Explore every episode of the podcast Manufacturing Hub
| Title | Pub. Date | Duration | |
|---|---|---|---|
| Ep. 277 - Inside the Siemens Pop Up Factory: How a Modular CPG Plant Runs Half Real and Half Virtual | 15 oct. 2026 | 01:10:35 | |
The Siemens pop up factory is a modular CPG plant where virtual PLCs, real controllers, and a live digital twin run small batches side by side. Most factories are built for long runs of the same product. Davide Picciotto explains why that model is being stretched. COVID supply chain shocks pushed brands to add flexible areas inside existing plants, and events like the World Cup raised a sharper question: what if a factory could be stood up close to demand, run personalized products for a season, and then move? Siemens is validating the idea with PepsiCo through what Davide calls a hybrid immersive prototype: half the factory is virtual, half is real, and both run as one system. Pininfarina, the design house behind decades of Ferraris, designed the modular shell. Andrea Sassetti walks through the live environment that debuted at Hannover Messe. Four PLCs, some physical and some virtual on Industrial Edge, feed the Industrial Information Hub, which adds a semantic layer and pushes data to the cloud. Virtual PLCs also simplify firmware and security patching. A capability matching engine reads each recipe step, checks which equipment is available and stocked with the right material, and routes the batch in real time. The same engine builds rainbow pallets of mixed product layers, using the Simatic robot library over SRCI so the same code runs on a Universal Robots cobot or any compatible arm. The most interesting idea is in the mixer. Traditionally, mix time and speed are hard coded into the recipe. Siemens ran thousands of Simcenter fluid dynamics simulations across viscosities, particle sizes, and impeller types, trained a model in AI Studio from the Altair RapidMiner acquisition, and deployed it on Industrial Edge. The recipe now specifies material properties, and the model infers setpoints on the fly, even when an ingredient comes from a new supplier. Davide closes on what is still missing: digital threads between engineering and execution remain incomplete, with one CPG company counting thousands of clicks to launch a single product. PepsiCo has reported a 20 percent throughput gain at a US Gatorade plant from its digital twin work with Siemens and NVIDIA. About the Guests Andrea Sassetti is an Innovation Manager on the Siemens Digital Enterprise team. He joined Siemens in 2009 as an MES developer on what is now Opcenter, then moved to the US in 2018 as solution architect for the Siemens showcase at MxD. Timestamps References This episode is sponsored by About Your Hosts Vladimir Romanov is a co-host of The Manufacturing Hub Podcast and the founder of Joltek, an independent manufacturing and industrial automation consulting firm specializing in modernization strategy, digital transformation, and workforce development. Joltek works with manufacturers and investors to de-risk modernization and build the internal capability to sustain results. Want to go deeper? Vlad and the team at Joltek have covered related topics here: Dave Griffith is a co-host of The Manufacturing Hub Podcast and founder of Capelin Solutions, an industrial automation firm helping manufacturers adopt smart manufacturing technology. He brings 15 years of experience in industrial automation and digital transformation. Subscribe to Manufacturing Hub: https://www.manufacturinghub.live | |||
| Ep. 274 - David Schultz on ISA 95, Knowledge Graphs, and Building a Data Model for AI | 17 sept. 2026 | 01:06:56 | |
There is no pyramid anywhere in the ISA 95 standard. David Schultz explains what is actually inside it and how to turn it into a working data model. Most engineers meet ISA 95 as a layered triangle on LinkedIn and never get past it. David Schultz of Amárach StackWorks takes that image apart. The pyramid appears nowhere in the standard, which exists to define how business systems such as ERP exchange information with manufacturing and control systems. Eight parts are published today, Part 1 refreshed in 2025, with Part 9 still in committee. Start with Parts 1 and 2. Part 1 sets the scope, Part 2 delivers the resource, information and process models. Parts 3 and 4 add the activity models and the work master. Parts 5 and 6 supply the verbs and exchange patterns. From there it collapses into a frame you can hold in your head: four resources of equipment, physical asset, personnel and material, four domains of production, maintenance, quality and inventory, and four exchanges covering definition, capability, schedule and performance. Use what works and leave the rest. On adoption David is candid. The full set runs roughly $1,400, and the paywall keeps it out of most LLM workflows because ISA would forfeit copyright by opening it up. Where it breaks is data governance. When every site builds bespoke models, stitching them together means inventing a fourth abstraction. Vlad offers a first hand version from Procter and Gamble, where nobody at plant level owned the data structure moving from Rockwell controls into Proficy. For brownfield sites the advice is the Strangler fig pattern: leave what runs and replace functionality over time. The second half demystifies knowledge graphs using a family tree. A graph stores a subject, a predicate and an object, and the relationship is a first class citizen, not a foreign key. RDF defines the things, RDFS adds schema, OWL adds inference so a system can derive siblings from a shared parent, and SHACL constrains the shapes. Applied to a tank, that means volume and level as properties plus the resource relationship network to map which pump feeds which vessel. Rhize implemented the entire 2018 standard as a graph. David stays cool on AI. A shared ontology means a model never guesses whether two names match, but he expects it to underwhelm. His book pick is The Semantic Web for the Working Ontologist. About David Schultz Timestamps References About Your Hosts Vladimir Romanov is a co-host of The Manufacturing Hub Podcast and the founder of Joltek, an independent manufacturing and industrial automation consulting firm specializing in modernization strategy, digital transformation, and workforce development. Joltek works with manufacturers and investors to de-risk modernization and build the internal capability to sustain results. Want to go deeper? Vlad and the team at Joltek have covered related topics here: Dave Griffith is a co-host of The Manufacturing Hub Podcast and founder of Capelin Solutions, an industrial automation firm helping manufacturers adopt smart manufacturing technology. He brings 15 years of experience in industrial automation and digital transformation. Subscribe to Manufacturing Hub: https://www.manufacturinghub.live | |||
| Ep. 273 - How to Build a Systems Integration Company: Positioning, Money and Procurement | 10 sept. 2026 | 01:22:36 | |
Most conversations about starting a systems integrator skip the parts that sink people. Dave and Vlad spend this one on insurance, licenses and procurement. After a month of founder interviews, Dave and Vlad close the series with their own experience. Vlad started at plant level with Procter and Gamble and Kraft Heinz, deciding how outside integrators would execute, before crossing over to work for an integrator across food and beverage and CPG packaging. Dave came from aviation and aerospace through a German machine builder and a distributor, then ran a small integration company doing MES, OEE and track and trace. Both reached the same conclusion. Integration starts after the requirements are written, so you quote to a spec and a budget, build the thing, and real handover rarely follows. Blame does not sit in one place. Vlad puts it plainly: people resent a solution that has not actually solved something for them. But end users say they do not need training and ask for the lowest number, and training is the first line cut. Dave counters that if a customer wants five dashboards on an ugly six inch HMI that has sat in the plant for fifteen years, that is the job. Vlad's answer is that your time is finite, and a year on work you cannot show anyone positions you as the person who does that work. The technical centerpiece is a migration that sounds nearly free. Moving from RSView 32 to FactoryTalk View gets justified because conversion tools exist. Then come the undocumented Visual Basic scripts written around tag limits on old controllers, which no conversion tool touches. Then the PLCs will not support the new terminals and servers, so the controllers go too. Then the networks underneath, often Data Highway Plus. Then servers, remote racks, IO, sensors and drives. Vlad argues these decisions get made by people who never price the second and third order effects. An integration firm is a service firm, billing time and materials or a fixed fee, with a markup on hardware and software. Vlad quotes roughly $200 a month for $2 million of liability coverage, a capable laptop, and software licenses reaching tens of thousands of dollars per seat without preferential pricing, usually several across PLC and HMI programming. Then procurement, which nobody warns new integrators about. Dave has cleared it in twenty minutes and has waited seven months, three or four of those with lawyers arguing over a master service agreement. Vlad closes on complexity. Industrial equipment no longer ships with a full schematic and a six dollar replacement sensor, so ramp up time climbs while the population who understand electrical, mechanical and process together shrinks as the best of them retire. Dave sees it from the other side. Entry now takes an LLC, a laptop and a phone, and he expects private equity to keep buying medium and large integrators over the next five years. Timestamps References About Your Hosts Vladimir Romanov is a co-host of The Manufacturing Hub Podcast and the founder of Joltek, an independent manufacturing and industrial automation consulting firm specializing in modernization strategy, digital transformation, and workforce development. Joltek works with manufacturers and investors to de-risk modernization and build the internal capability to sustain results. Want to go deeper? Vlad and the team at Joltek have covered related topics here: Dave Griffith is a co-host of The Manufacturing Hub Podcast and founder of Capelin Solutions, an industrial automation firm helping manufacturers adopt smart manufacturing technology. He brings 15 years of experience in industrial automation and digital transformation. Subscribe to Manufacturing Hub: https://www.manufacturinghub.live | |||
| Ep. 272 - Systems Integration Careers: OEM, Distributor, Machine Builder and Business Owner | 03 sept. 2026 | 01:28:37 | |
Most people ask how to start a systems integrator. Rich Kuechenmeister has effectively built one five times, and the lesson is that the parent business decides what you become. Rich is owner and partner at Fishbone Technical Services. Before that he built automation groups inside a semiconductor equipment OEM, an automation components manufacturer, a products distributor, and a custom machine builder where he stood up a UL 508A panel shop from nothing. Each of those businesses sold something different, and that changed the engineering. At a machine builder the machine is the dog and the controls are the tail. At a distributor you build toolkits so somebody else can build the solution, handcuffed to the lines you carry. Rich argues that constraint is what made him good, because a single vendor solution is easy while four component areas from four vendors is where real integration lives. His definition of a control systems integrator stays traditional. SCADA and below, field instrumentation through PLC and HMI, bridging a little into MES. Fishbone works line control, process control on boilers, pumps and valves, and material handling where suppliers ship a motor and a few sensors and nothing more. The business advice is specific. He would rather have one $100,000 project than ten $10,000 projects, because that is one project management cycle instead of ten. He cautions against mixing maintenance work and capital projects without a plan, since context switching between a vision system callout and a pump control program burns budget on both. Dave adds the pattern he keeps seeing: come in at the bottom and you get saved in the phone as the maintenance guy, never the capital project guy. Rich hires on desire, attitude and aptitude, and admits he was once the bottleneck himself. Looking ahead, he expects acquisitions to keep rolling up integrators and leaving a void underneath, since a twenty person firm will not get out of bed for the projects a five person firm lived on. On AI he is practical. He turned three day estimates into eight estimates in a single day, but insists code writing is a subset of the job. He is also still doing a PLC-5 conversion and a DeviceNet upgrade. About Rich Kuechenmeister Rich Kuechenmeister is owner and partner at Fishbone Technical Services, a nationwide remote technical services company he co-founded in 2021 with business partner Robert Summers. Fishbone is based in Texas and covers plant engineering and control systems integration from field instrumentation through PLC, HMI and SCADA, with some MES. Rich began his career in the United States Navy working on radars, servos and guidance systems, then spent three decades in industrial automation building engineering groups before starting Fishbone. Timestamps References About Your Hosts Vladimir Romanov is a co-host of The Manufacturing Hub Podcast and the founder of Joltek, an independent manufacturing and industrial automation consulting firm specializing in modernization strategy, digital transformation, and workforce development. Joltek works with manufacturers and investors to de-risk modernization and build the internal capability to sustain results. Want to go deeper? Vlad and the team at Joltek have covered related topics here: Dave Griffith is a co-host of The Manufacturing Hub Podcast and founder of Capelin Solutions, an industrial automation firm helping manufacturers adopt smart manufacturing technology. He brings 15 years of experience in industrial automation and digital transformation. Subscribe to Manufacturing Hub: https://www.manufacturinghub.live | |||
| Ep. 271 - Growing an Oil and Gas Plus Mining Systems Integrator in Alberta with JPI Solutions | 27 août 2026 | 01:11:40 | |
Oil and gas automation runs on royalty accounting as much as process control. Dustin Symes explains how that shapes every SCADA decision JPI Solutions makes. Canadian oil and gas is structured differently than most assume. In the US mineral rights usually sit with individuals, so custody transfer draws a hard line between upstream and midstream. In Canada the provinces hold most rights, so a producer can gather 100 wells into one plant and sell to a pipeline company there. That lands on the automation: much of the SCADA data collection exists to answer who is paying whom and how much royalty is owed. Once a well is drilled, automation might find 5 to 10 percent off nameplate, so the work protects a long production tail rather than chasing throughput. Mining behaves nothing like it. Thinner margins, $100 million capital projects, an hour long elevator ride down, underground space running 20 miles across. Those are small cities: control systems cover substations, air monitoring and lighting as well as conveyors and pumps. Mining clients want programmers on site rather than remote, and they buy for continuity: a major vendor PLC paired with their DCS, meant to last 20 years. Horizontal drilling has rescaled oil and gas, from one well and a dozen sensors to a 32 well pad carrying 300 IO, pushing designs toward redundant PLCs and ring networks. The genuinely new technology lands on the data layer, where MQTT and report by exception are displacing polled Modbus. Dustin set two gates before his first hire: enough cash banked to make that person whole for a month or two, and enough overload to have work worth delegating. He hired out of the instrumentation program at SAIT rather than a 15 year instrument mechanic. When he weighed taking on partners, dozens of people advised against it. He brought in Dan and Brent Lawther anyway in 2018, went from five people that spring to ten by the fall, and says JPI would not exist without them. His hardest won lesson is unglamorous. Communication is the only consistent complaint he has ever had from a customer. Nobody complains about the code. They complain that nobody told them it was finished. On AI, JPI is decompiling Rockwell files into shutdown keys and landing 85 to 90 percent of the way there on a good prompt, and running log analysis across FactoryTalk directory, HMI and historian logs to find real root causes. He expects PLC code to become text so it can be version controlled like software, and customers to treat that as baseline within five years. About Dustin Symes Dustin Symes is Chief Technology Officer at JPI Solutions, a Calgary based systems integrator serving oil and gas and mining clients across North America from four offices in Alberta, BC and Saskatchewan. A Red Seal journeyman electrician who moved into automation, he founded JPI in 2017. JPI covers process control from the sensor to the HMI, then up into SCADA and corporate data. Timestamps References About Your Hosts Vladimir Romanov is a co-host of The Manufacturing Hub Podcast and the founder of Joltek, an independent manufacturing and industrial automation consulting firm specializing in modernization strategy, digital transformation, and workforce development. Joltek works with manufacturers and investors to de-risk modernization and build the internal capability to sustain results. Want to go deeper? Vlad and the team at Joltek have covered related topics here: Dave Griffith is a co-host of The Manufacturing Hub Podcast and founder of Capelin Solutions, an industrial automation firm helping manufacturers adopt smart manufacturing technology. He brings 15 years of experience in industrial automation and digital transformation. Subscribe to Manufacturing Hub: https://www.manufacturinghub.live | |||
| Ep. 270 - How to Start a Systems Integrator: Scope, Hiring, and the Bottleneck That Is You | 20 août 2026 | 01:15:05 | |
Most people who start a systems integrator expect to keep doing the engineering. Dylan DuFresne explains why that stops being true inside two years. Ask ten people what a systems integrator is and you get ten answers, so Dylan DuFresne starts from first principles: a third party that connects systems which used to sit isolated. The market then splits in two. One is the generalist who has seen a hundred platforms across a thousand facilities and knows how they behave together. The other is the specialist who lives inside one or two stacks. If you know what you are building, hire the specialist. If you are still deciding, the generalist saves you money. Abelara exists because of a pattern Dylan hit repeatedly during more than a decade inside other integrators. By the time a client calls, the platform is chosen, the budget is set, and the outcome is locked in, even when that platform cannot deliver it. His answer was to move upstream into architecture, change management, and business process work with VPs and C suite sponsors. His first question is always why. Why this site, why this machine, why this platform, and what outcome is attached to it. With no clear scope of work, Abelara declines to bid or sells the consulting engagement that produces one. When scope is fuzzy but workable he prices it all in and writes explicit exclusions and assumptions up front. His test before a proposal is one question: what does done look like. A striking number of buyers cannot answer it. He also corrects an instinct: a $200 sensor may beat a $30,000 camera technically and still be the wrong call, because the expensive option is a known quantity and carries less risk. Scaling gets treated as line balancing applied to a company. Find the bottleneck, find the gap in skills or availability, and staff it. Each hire moves the constraint somewhere new, and the hardest part is emotional: letting go of work you enjoy and are good at. On AI, Dylan predicts integration goes back to being integration. A generation of integrators drifted into custom coding, with companies of 400 and 500 people building MES and SCADA stacks from scratch, and he expects code generation to strip that work away. Writing a tool that pulls PLC data to the cloud is easy. Running it reliably and securely 24/7 for a year is not. About Dylan DuFresne Timestamps References About Your Hosts Vladimir Romanov is a co-host of The Manufacturing Hub Podcast and the founder of Joltek, an independent manufacturing and industrial automation consulting firm specializing in modernization strategy, digital transformation, and workforce development. Joltek works with manufacturers and investors to de-risk modernization and build the internal capability to sustain results. Want to go deeper? Vlad and the team at Joltek have covered related topics here: Dave Griffith is a co-host of The Manufacturing Hub Podcast and founder of Capelin Solutions, an industrial automation firm helping manufacturers adopt smart manufacturing technology. He brings 15 years of experience in industrial automation and digital transformation. Subscribe to Manufacturing Hub: https://www.manufacturinghub.live | |||
| Ep. 269 - Siemens Xcelerator Marketplace: Digital Transformation SMB Manufacturers Can Afford | 13 août 2026 | 01:13:53 | |
Siemens says a small manufacturer can start production optimization for $2,000 a year. Martin Valkysers and Flemming Kongsberg explain what that buys you. Most digital transformation advice assumes a budget and an engineering bench most plants do not have. Flemming Kongsberg, who runs the SMB focus inside the Siemens CTO organization, discards the usual revenue and headcount definitions: an SMB is any manufacturer without the skills to absorb a complex digital change, and that includes some very large companies. He describes one customer running 900 devices across 17 locations where 90 percent of the machines are 30 years or older with zero connectivity. Siemens research also found 40 percent of SMB customers have no IT department. Martin Valkysers frames Siemens Xcelerator as the open digital business platform tying hardware, software, data, and services together, with more than 600 partners today. The SMB starter package is where that becomes concrete. Instead of asking a plant with no IT staff to assemble something from hundreds of apps, Siemens curated roughly 10 to 12 into one bundle covering device connectivity, Performance Insight dashboards for OEE and quality, and a slice of Mendix. A partner installed it in a lab in 24 minutes on an ordinary Windows machine, against the roughly 60 hours a traditional Industrial Edge deployment takes. It is $2,000 per year for three machines with the first three months free, and PROFINET, Ethernet/IP, and the standard protocols are supported, so competitor PLCs connect too. The most useful argument here has nothing to do with buying anything. Flemming makes the case that reaching for AI before you own your data is a losing move, because a model built on information everyone else can reach produces no strategic advantage. You also do not need AI to build a Pareto chart of where your quality losses sit. Martin adds the discipline that gets skipped most: be clear about the problem before you pick the tool. About the Guests Martin Valkysers is Head of US Market Launch and Growth for Siemens Xcelerator, Siemens' open digital business platform spanning industrial, building, grid, and manufacturing sectors. He has been with Siemens roughly 12 years, previously leading a US operations consulting team focused on lean manufacturing. Flemming Kongsberg leads Global Technology Partners at Siemens Digital Industries Software and runs the company's SMB focus in the US. Before Siemens he spent nearly eight years at Amazon Web Services building partner infrastructure and strategic ISV alliances. Timestamps References This episode is sponsored by About Your Hosts Vladimir Romanov is a co-host of The Manufacturing Hub Podcast and the founder of Joltek, an independent manufacturing and industrial automation consulting firm specializing in modernization strategy, digital transformation, and workforce development. Joltek works with manufacturers and investors to de-risk modernization and build the internal capability to sustain results. Want to go deeper? Vlad and the team at Joltek have covered related topics here: Dave Griffith is a co-host of The Manufacturing Hub Podcast and founder of Capelin Solutions, an industrial automation firm helping manufacturers adopt smart manufacturing technology. He brings 15 years of experience in industrial automation and digital transformation. Subscribe to Manufacturing Hub: https://www.manufacturinghub.live | |||
| Ep. 268 - David Nichols of Loupe on Claude Code, AI Retrofits, and the End of the SI Moat | 06 août 2026 | 01:08:01 | |
David Nichols of Loupe explains what actually changed in automation engineering this year, and why control retrofits just got far cheaper. Nearly twenty years into building high performance controls, David Nichols is blunt about what AI did to his business: what used to take six weeks now takes two, and his team ships roughly five times more software per sprint. An engineer dropped the raw documentation from a failing robotic cell into a folder, asked Claude for a state diagram, and got a reverse engineered flow chart in thirty minutes that beat anything the customer had. The error recovery gap causing the downtime was visible right there in the chart. A SASE member handed a model a hundred page ethernet specification and got working code for every function, plus tests, on the first try. That was a six week project. It took a day. The implication is the sharpest part of the conversation. Software rewrites used to be the dumbest thing an engineer could propose, because software was expensive and full of unknowns. That logic has inverted. If a rewrite takes a week and produces better documentation, better tests, and better coverage, then brownfield modernization stops being a risk calculation. His words: open season on old controllers. For an industry sitting on Windows 7 machines and undocumented cells one PC failure away from stopping a line, that is a different economic picture entirely. Vlad walks David through the full project lifecycle, and the answers stay practical. Discovery becomes a context gathering exercise where interview transcripts and a drawer full of legacy PDFs turn into control diagrams and proposals in days. Development becomes worth treating as a real software engineering project, because source control, digital twins, and automated testing are exactly what these models are fluent in. David is equally direct about platforms: the bottleneck in automation was never technical, it is cultural. His analogy is a shop that insists on carburetors because that is what the technicians know. The close tackles the chat's harder questions, including what is left of a software moat once building software is trivial. His book pick is Richard Rhodes and The Making of the Atomic Bomb. About David Nichols Timestamps References About Your Hosts Want to go deeper? Vlad and the team at Joltek have covered related topics here: Dave Griffith is a co-host of The Manufacturing Hub Podcast and founder of Capelin Solutions, an industrial automation firm helping manufacturers adopt smart manufacturing technology. He brings 15 years of experience in industrial automation and digital transformation. Subscribe to Manufacturing Hub: https://www.manufacturinghub.live | |||
| Ep. 267 - Ujjwal Kumar of Siemens on Deglobalization, Reshoring, and Adaptive Manufacturing | 30 juil. 2026 | 01:02:23 | |
Deglobalization is rewriting where factories get built, and Ujjwal Kumar of Siemens explains what has to change on the plant floor before reshoring actually works. For thirty years the manufacturing playbook was labor arbitrage. Move high volume, low mix production to wherever disciplined labor was cheapest, then ship it back. Ujjwal Kumar, President of Automation for Siemens Digital Industries in the Americas, argues that model has quietly stopped making sense. Demand has fragmented into high mix, lower volume, regionally specific production, and the factories in Suzhou running on robots and autonomous systems no longer carry a cost advantage over the same operation in Chicago. When the labor content collapses, the business case for distance collapses with it. That single shift explains more about the current reshoring wave than any tariff headline. The trigger was not one event. Supply chain disruption after COVID proved that geographic proximity to supply was a profitability advantage, not a nice to have. Then came the political shock: vaccine access turned out to be governed by country of citizenship rather than global distribution, and leaders across every region started sorting industries into a folder marked critical. That folder now holds semiconductors, steel, power generation, defense, space, and life sciences. Ujjwal walks through where the money is actually landing right now, including AI data centers in remote locations that demand autonomous and remote operations, power generation across fossil, renewable, nuclear, and hydro, and a level of greenfield life sciences investment in the United States he has not seen in decades. The life sciences point is the sharpest one in the episode. Drug manufacturing left as mass produced batch operations and is returning as cell and gene therapy, personalized medicine, and precision biologics, which means lot sizes of one and R&D sitting physically next to production. The design it here, build it there model taught in business schools simply does not survive that. About Ujjwal Kumar Timestamps References This episode is sponsored by About Your Hosts Want to go deeper? Vlad and the team at Joltek have covered related topics here: Dave Griffith is a co-host of The Manufacturing Hub Podcast and founder of Capelin Solutions, an industrial automation firm helping manufacturers adopt smart manufacturing technology. He brings 15 years of experience in industrial automation and digital transformation. Subscribe to Manufacturing Hub: https://www.manufacturinghub.live | |||
| Ep. 266 - Automate 2026 Reality Check: AI, Virtual PLCs, Ignition, and Plant Modernization | 18 juil. 2026 | 01:27:57 | |
After several weeks away from the podcast, Dave Griffith and Vladimir Romanov return to Manufacturing Hub to unpack their experiences at Automate 2026 and discuss what the event revealed about the current state of industrial automation. Automate showcased an enormous range of robotics, industrial AI, machine vision, software, cloud connectivity, and emerging automation technology. However, some of the most revealing conversations were not about futuristic factories. They were about PLC 5 migrations, aging SLC systems, obsolete PanelView terminals, industrial networks, basic data collection, and how platforms such as Ignition actually connect to plant floor equipment. Vlad shares what he learned from demonstrating a complete packaging line environment built around a CompactLogix PLC, an industrial computer, Ignition, and production performance data. The demonstration was designed to show how manufacturers can use OEE, downtime information, and machine states to identify production bottlenecks and determine where capital investment could deliver the greatest return. Instead, many attendees wanted to understand the underlying architecture, where Ignition runs, how it connects to PLCs, what protocols are required, and whether it can replace traditional HMI and SCADA platforms. Dave discusses his experience inside the Ignition ecosystem booth, the FactoryStack cloud demonstration, the advantages of MQTT in a difficult trade show network environment, and his Automate panel on software defined automation and the factory of the future. He also introduces Elephant, an industrial log analysis and contextualization tool being developed to help users identify meaningful patterns across Ignition gateways, reduce system noise, compare facilities, and diagnose intermittent problems. The conversation then moves across the industrial automation stack. Dave and Vlad examine virtual PLCs from Siemens, Phoenix Contact, and other vendors, including where software based control may provide value and where it may add unnecessary organizational complexity. They discuss AI generated PLC code, the limitations of translating functional specifications into reliable control applications, and why tools that produce 80 or 90 percent of an automation solution still require experienced engineers to validate the final result. They also explore AI assisted HMI and SCADA development, Ignition 8.3, MCP servers, high performance HMI design, and the risks of providing AI agents with uncontrolled access to production systems. At the MES layer, they question whether manufacturers should build custom applications through vibe coding or focus instead on creating clean, contextualized, well governed data that can support many future applications. The central conclusion is that AI tools, virtual controllers, cloud platforms, and dynamically generated applications will continue to improve. However, manufacturers still need reliable controls, secure networks, maintainable architectures, experienced people, and ownership of their operational data. The companies that establish those foundations today will have the greatest freedom to adopt whatever technologies emerge next. Dave and Vlad also preview the 2026 Ignition Community Conference in Sacramento, upcoming Manufacturing Hub conversations, new demonstrations, and several projects the community will see throughout the remainder of the year. Join us for a detailed and candid discussion about Automate 2026, Ignition, industrial AI, virtual PLCs, HMI and SCADA development, MES, MQTT, data architecture, and what manufacturers should prioritize next. | |||
| Ep. 265 - Automate 2026 Survival Guide: Booths, Networking, and a Production Line Demo #scada #mes | 18 juin 2026 | 00:35:02 | |
Automate 2026 lands in Chicago next week, and Dave and Vlad break down how to work the show floor, where to network, and what to expect from their live booth demos. Automate is the largest automation trade show in North America, and a four day event rewards preparation. Dave and Vlad share tactics refined over five years of attending together. The floor opens at 10:00 AM on Monday, and registration lines have swung from a five minute wait to nearly two hours, so arriving early matters. Monday morning and Thursday are the quietest days to reach specific vendors, while Tuesday and Wednesday draw the heaviest crowds. The hosts also favor the official show app over a paper map for finding booths and session rooms across multiple halls. The real value of a show like Automate often lives in the networking. Dave points to the A3 networking event on Monday, a ticket of roughly 45 dollars, and the Manufacturing Champions happy hour on Tuesday organized by Chris Luckey and Jake Hall. Vlad's advice is structural: build a checklist before you arrive. He researches each company, finds the booth number, and tracks every connection in a spreadsheet so the week becomes a series of deliberate meetings instead of aimless wandering. For anyone with ten or more booths on their list, setting up meetings in advance is the highest leverage move you can make. The centerpiece of the conversation is the live demo Vlad built for the Teguar booth. It pairs a Rockwell CompactLogix PLC with an Ignition gateway running on a Teguar industrial PC, and it simulates a food and beverage packaging line with five assets: filler, capper, labeler, case packer, and palletizer. The line overview screen shows real machine states including faulted, starved, backed up, and running, and the whole point is to make the bottleneck visible. When the case packer needs six bottles from the labeler but the labeler cannot keep pace, you watch the downstream asset flip between starved and running in real time. It is a practical illustration of why line balancing and constraint analysis drive real ROI on a production floor. Under the hood the stack is modern. The Teguar IPC runs Ubuntu with Portainer managing containers for Ignition 8.3, Ignition 8.1, and a MariaDB database for alarm history. Ignition 8.3 ships new drivers for Rockwell, Siemens, Mitsubishi, and Omron controllers along with OPC and MQTT, and each asset carries ten randomized faults written in both Ignition and PLC logic. Vlad built it for everyone from engineers to the decision makers running SCADA and MES projects. Dave and Vlad will also shoot content at the Siemens booth on Tuesday and the Horner Automation booth on Wednesday, and Dave is moderating a Wednesday session on software defined automation and the factory of the future. Timestamps References About Your Hosts Want to go deeper? Vlad and the team at Joltek have covered related topics here: Dave Griffith is a co-host of The Manufacturing Hub Podcast and founder of Capelin Solutions, an industrial automation firm helping manufacturers adopt smart manufacturing technology. He brings 15 years of experience in industrial automation and digital transformation. Subscribe to Manufacturing Hub: https://www.manufacturinghub.live | |||
| Ep. 264 - Why AI Loves Automation: Siemens on Digital Twins, Guardrails, and Orchestration | 11 juin 2026 | 01:04:14 | |
AI can finally write back to the plant floor, but only if you can trust it. Chris Stevens and Annemarie Breu of Siemens explain how orchestration makes that safe. Industrial AI has reached a turning point. Manufacturers can already collect data, contextualize it, and surface insights, but the hardest step has always been turning insight into action on real control equipment. Chris Stevens and Annemarie Breu of Siemens explain how an orchestration layer finally closes that loop. Annemarie frames the tension clearly. Automation depends on determinism, while large language models are probabilistic by design, so the goal is to bring that discipline into AI and validate any suggestion before it changes a set point. Most executive conversations start with return on investment, and two forces are making the case easier to prove. The workforce shortage has stretched the expected payback window from 18 months toward 36 months, and when a line cannot run for lack of people every idle minute costs thousands of dollars. The other driver is overall equipment effectiveness, since most plants run near 70 percent OEE and even a fraction of a percent of gain can justify a project. Energy is a standout case too. A BorgWarner sustainability effort used a digital twin to flatten demand peaks and reportedly paid for itself in under six months, even as data center growth pushes electricity demand higher through 2040. On trust and safety, Annemarie borrows a principle from industrial safety. Just as fail safe IO modules rely on two channel evaluation, every AI suggestion is validated against a state machine, a workflow, or a physics based digital twin before the orchestration layer passes it to a controller. With virtual commissioning and soft PLCs a change can be tested virtually, approved by a human in the loop, and only then written to control, an approach PepsiCo and NVIDIA echoed at CES when they called the digital twin a must have. Making AI real, the pair argue, comes down to discipline, clear scope, acceptance criteria, and focused 90 day challenges, plus the change management and user experience that drive adoption. Their favorite quick win is preventive maintenance driven by machine data, which both BorgWarner and Maersk tied to millions in savings. About Chris Stevens About Annemarie Breu Timestamps About Your Hosts Want to go deeper? Vlad and the team at Joltek have covered related topics here: Dave Griffith is a co-host of The Manufacturing Hub Podcast and founder of Capelin Solutions, an industrial automation firm helping manufacturers adopt smart manufacturing technology. He brings 15 years of experience in industrial automation and digital transformation. Subscribe to Manufacturing Hub: https://www.manufacturinghub.live | |||
| Ep. 263 - Why Industrial Protocols Win on Business Not Technical Merit, with Horner Automation | 04 juin 2026 | 01:03:57 | |
Industrial network protocols decide whether a machine talks or stays silent. Chuck from Horner Automation breaks down how they win, fade, and converge. Chuck has spent 36 years at Horner Automation and lived through what the industry once called the fieldbus wars. Before Horner became known for its all in one controllers, it spent a decade building specialty IO modules for GE Fanuc during the era of DeviceNet, SDS, InterBus S, PROFIBUS, and CANopen. His core argument is that most of those early protocols were technically fine. The ones that became standards won on the commercial weight of the companies backing them, not on superior specifications, with EtherCAT a rare exception that succeeded largely on technical merit. Trust is the recurring theme. Industry adopts slowly, and for years Ethernet was dismissed as too unreliable and not deterministic enough for control until Ethernet/IP, PROFINET, and Modbus TCP proved themselves. Today the market has settled around a big four set of protocols, and Chuck does not expect it to narrow further. For high speed motion he points to EtherCAT and PROFINET IRT as the implementations he most respects, since both step away from standard Ethernet at the device level to reach submillisecond timing. The episode is also a reality check on building your own hardware. Chuck and Dave describe how custom development routinely costs teams hundreds of thousands to millions of dollars, and how the real trap is obsolescence and maintenance rather than the first build. On the product side, the standout is FPD-Link, a serialization technology borrowed from automotive that carries video, touch, and power over one coaxial cable. Working with Safe Fleet, a maker of ambulances and fire trucks, Horner now mounts rugged displays up to seven meters from the PLC while still programming everything as one device. Looking ahead, Chuck argues that every PLC should now be treated as a data device first, because digitizing the process is the prerequisite for doing anything useful with AI. He also flags cybersecurity as the next burden for application engineers, with new mandates forcing both manufacturers and integrators to implement protections that were once optional. At Automate, Horner is showing HMI Connect and a 300 dollar CPU 151 that packs 18 IO points, wireless connectivity, and edge capability into a micro PLC. About Chuck and Horner Automation Timestamps References About Your Hosts Want to go deeper? Vlad and the team at Joltek have covered related topics here: Dave Griffith is a co-host of The Manufacturing Hub Podcast and founder of Capelin Solutions, an industrial automation firm helping manufacturers adopt smart manufacturing technology. He brings 15 years of experience in industrial automation and digital transformation. Subscribe to Manufacturing Hub: https://www.manufacturinghub.live | |||
| Ep. 262 - The Human Side of Manufacturing Change: Incentives, Pain Points, and Operator Buy In | 28 mai 2026 | 01:05:27 | |
Change management is the reason most manufacturing improvement projects quietly stall, even when the technical work is sound and the tools are right. Vlad Romanov and Dave Griffith unpack their own change management war stories from across two decades in industrial automation. Vlad frames change management as understanding risk to the business and to every stakeholder, then putting the process in place that lets the organization absorb that risk. Technical feasibility is the easy half of any project. Getting humans to consistently work the new way is the half that wins or loses the budget. Vlad joined Procter & Gamble at a site rated four on P&G's Integrated Work Systems maturity scale, the highest in North America at the time. Every loss event triggered a structured root cause analysis cascade. Operator, mechanic, operations engineer, and only then the engineering department. He later moved to Kraft Heinz, which had purchased the same IWS toolkit from P&G. The tools were on the shelf. The site rating was effectively zero. He had spent his early career learning to use the tools without having to deploy them, and that gap is where most transformation programs die. Dave's lens is more political. Change management starts with one question engineers rarely ask. What is in it for the person you are asking to change? He tells the Joe story, a lead operator with more than 35 years on the floor who interrupted a connected workforce rollout meeting to point out that his team had cycled through every methodology fad of the last two decades. None had stuck. Dave's team asked what hurt the most. Joe kept training new operators who left for a dollar an hour more down the street. The fix was QR codes on equipment linked to procedures Joe recorded once. Joe went from skeptic to evangelist in one session. Find the operator with the deepest tenure, solve their pain, and let them carry the change. The episode is also honest about what well intentioned incentives do when they miss the mark. Vlad walks through an RCA rollout where management offered a fifty dollar gift card to whoever submitted the most reports each week. The team got a stack of paper. None of it shortened downtime. When real process change goes through a plant, throughput typically drops twenty to thirty percent for weeks or months. That cost has to be visible to leadership before the project starts. Two practical heuristics close the episode. As a systems integrator deploying MES and SCADA across food and beverage plants, Vlad could often predict success within the first demo by how the room reacted. Continuous improvement teams leaned in. Whiteboard sites pushed back. Dave reinforces that change has to start at the top. If the executive sponsor blows off steering meetings, the floor reads that signal. Change management is a habit, not a project, and habits are built small. Pick one workflow, prove it works, and let the next one earn its slot. Timestamps About Your Hosts Want to go deeper? Vlad and the team at Joltek have covered related topics here: Dave Griffith is a co-host of The Manufacturing Hub Podcast and founder of Capelin Solutions, an industrial automation firm helping manufacturers adopt smart manufacturing technology. He brings 15 years of experience in industrial automation and digital transformation. Subscribe to Manufacturing Hub: https://www.manufacturinghub.live | |||
| Ep. 261 - Change Management in Manufacturing: Operators, Tribal Knowledge, and the Industrial Elder | 21 mai 2026 | 01:02:51 | |
Change management in manufacturing breaks down at the people layer, not the technology layer. This episode explains how engineering leaders actually drive adoption. Ronald Sherrod is a Staff Automation Engineer at Regeneron deploying a global event based architecture and Unified Namespace rollout across pharmaceutical operations. Ron, Vlad Romanov, and Dave Griffith dig into the parts of change management that rarely make it onto vendor decks. Subscribe to Manufacturing Hub for weekly conversations with industrial automation practitioners. Want to go deeper? Vlad and the team at Joltek have covered related topics here: Ron makes a point that is rarely stated this directly. The organization implementing the change is the one responsible for it. OEMs and system integrators deliver the box. Consultants help interpret it. Auditors do not call the machine builder when something goes wrong on the floor of a regulated pharmaceutical plant. They walk into the manufacturer and ask whether the audit trails hold up, whether the predicate rule was met, and whether the product is safe for patients. That responsibility cannot be outsourced, even when the technical work is. That framing changes how engineering managers should think about RFP scope. If the scope is loose, the integrator absorbs the risk and prices accordingly. If the scope is rigorous, bids come back tight and comparable. Negotiating power changes with the size of the buyer. A large pharmaceutical company can dictate hypercare windows, on site commissioning support, and structured training. A small to mid sized manufacturer often cannot, and the result is the metaphorical Ferrari on the plant floor that only ever gets used for grocery runs. Capital was deployed. The technology works. The operation never adopted it. The episode also goes deep on tribal knowledge and the industrial elder, the technical anchor who carries the institutional history of a unit or process and is often more valuable than the Excel file on a network drive. Senior operators know why a pipe was rerouted fifteen years ago and why a procedure looks irrational on paper but works perfectly in practice. With 59 percent of frontline skilled workers over 55 planning to retire within five years per the Schneider Electric 2024 workforce survey, capturing that knowledge is now a leadership priority, not an engineering task. On planning, Ron walks through how he runs user story workshops with operators, manufacturing leaders, engineers, and developers in the same room, producing a shared data contract that defines what information moves where, who needs it, and why. He cites a successful SCADA deployment that worked because the organization had inertia, operators had asked for the problem to be solved, and the team was closing a real gap rather than chasing a trend. Ronald Sherrod is a Staff Automation Engineer at Regeneron, a chemical engineer by training who moved from oil and gas into pharma and now works on event driven architecture, UNS, and robotics initiatives. Ron: https://www.linkedin.com/in/rdsherrod/ Timestamps About Your Hosts Dave Griffith is a cohost of The Manufacturing Hub Podcast and founder of Capelin Solutions, an industrial automation firm helping manufacturers adopt smart manufacturing technology. Subscribe to Manufacturing Hub: https://www.manufacturinghub.live | |||
| Ep. 260 - Why Ignition Is Winning: Colby Clegg and Carl Gould on SCADA, Open Access, & Industrial AI | 14 mai 2026 | 01:10:36 | |
Inductive Automation cofounders Colby Clegg and Carl Gould go deep on the origins of Ignition, the road to 8.3, and what AI means for industrial automation. Vlad and Dave host Colby Clegg, CEO, and Carl Gould, CTO, of Inductive Automation together for the first time to trace the full arc of the company. The story begins in 2003, when Sacramento systems integrator Steve Heckman brought Colby and Carl in to build the missing glue layer between OT data and modern IT tooling. What began as logging values into SQL databases became Factory PMI and eventually Ignition. A key thread is why Ignition broke through when larger automation vendors had superior distribution. Colby points to Clayton Christensen's Innovator's Dilemma. Incumbents could not match Inductive's unlimited per gateway pricing or partner with integrators because their own services groups competed with them. Carl adds the culture piece. Inductive refused to gate downloads, kept the module SDK open, made education free, and ran a public forum when competitors called it reckless, a posture they once called innovation without permission. Ignition 8.3 takes center stage, arriving after a deliberate five year gap from 8.1. Carl frames it as the completion of work that began with 8.0 in 2018. Gateway configuration is now stored in open, readable formats on disk, the gateway web interface was rewritten, and the platform supports orchestration, environmental separation, and infrastructure as code workflows Carl expects to become table stakes. The release also adds event streams, a revamped historian, and perspective drawing tools. For integrators still on 8.1, 8.3 is the version built for distributed deployments across many gateways. On AI, Carl is candid that the new MCP server module is intentionally a minimum viable product. It ships as a raw toolkit for integrators to author MCP primitives that expose Ignition data to agentic systems like Claude Code. First party MCP tools are coming, but Inductive wants to define the guardrails before shipping an API surface they will support for years. Carl frames AI as a new axis of software possibility, comparable to the shift from DOS to Windows. Colby ties it back to legacy SCADA conversion, framing the security and reliability gains as a national security issue. The episode closes with notes on the Inductive ecosystem, including a new collaboration with Tiger Data behind TimescaleDB, plus career advice on soft skills, context, and agentic coding tools. About Colby Clegg and Carl Gould Timestamps References About Your Hosts Want to go deeper? Vlad and the team at Joltek have covered related topics here: Dave Griffith is a cohost of The Manufacturing Hub Podcast and founder of Capelin Solutions, an industrial automation firm helping manufacturers adopt smart manufacturing technology. He brings 15 years of experience in industrial automation and digital transformation. Subscribe to Manufacturing Hub: https://www.manufacturinghub.live | |||
| Ep. 259 - Logan Terry of LSI on Change Management: The Soft Side of SCADA, MES, & ERP Projects | 07 mai 2026 | 01:08:00 | |
Change management decides whether your MES or digital transformation project lasts, or quietly gets shut off six months after go live. Vlad Romanov and Dave Griffith sit down with Logan Terry, who leads digital transformation at LSI, to dig into change management as the deciding factor in any automation or MES rollout. Logan defines change management as a methodical approach to moving an individual, team, or organization from a current state to a desired future state. The closer a system sits to where decisions are actually made, the more change management it requires, which is why MES is the single hardest place to land a project successfully. Much of the episode digs into why change management is rarely scoped properly. In competitive RFPs, the integrator who includes a robust change management line item often loses to the lowest bid, and end users frequently do not know how to evaluate that line item even when it is offered. Logan starts every client engagement with a direct question: what does your continuous improvement practice look like internally? If the client cannot sustain the change after handover, the project is on borrowed time no matter how clean the FAT and SAT looked. Logan walks through one of the most useful failure stories on the show this year. His team delivered a technically perfect OEE dashboard for a production line. Six to nine months later, every terminal was shut off. The postmortem surfaced two missed details. Maintenance was never folded into the design, and a single failed photo eye broke throughput calculations with no manual reconciliation path, which destroyed operator trust in the data. The second miss was behavioral. Showing a 30 percent OEE against a 90 percent ideal demotivates the floor, while reframing the same number as 80 percent of a realistic 36 percent target turned out to be a cleaner motivator. Looking forward, Logan sees vendors moving away from monolithic 14 function MES suites toward modular, use case specific deployments, which compresses change management scope from twenty five workflows to five or six. On AI, he argues that managing generative agents in production is closer to managing a team of people than managing software, with continuous validation replacing one time qualification. He cites the line that AI does not make bad data worse, it makes it more convincing. LSI now uses AI assisted coding agents and React based prototypes to shrink design cycles from three or four weeks of Figma work down to three or four days. About Logan Terry Timestamps About Your Hosts Want to go deeper? Vlad and the team at Joltek have covered related topics here: Dave Griffith is a co-host of The Manufacturing Hub Podcast and founder of Capelin Solutions, an industrial automation firm helping manufacturers adopt smart manufacturing technology. He brings 15 years of experience in industrial automation and digital transformation. Subscribe to Manufacturing Hub: https://www.manufacturinghub.live | |||
| Ep. 258 - Hannover Messe Recap, the State of Industrial AI, and What Comes Next at Automate 2026 | 30 avr. 2026 | 01:08:14 | |
Industrial AI is moving past the chatbot phase. From the Hannover Messe show floor to system integration workflows, here's what end users actually want now. Vlad just returned from his first Hannover Messe, the largest industrial automation and manufacturing trade show in Europe. The takeaway that defined the week was a shift in how end users open conversations. A year ago, every booth visit started with the question, do you have AI? This year every vendor has some flavor of AI, so the question has flipped back to the one that actually matters. How does your product solve a specific problem in my plant? Vlad and Dave unpack what that shift means for vendors, integrators, and the end users buying these tools. On the end user side, the reality is mixed. Most knowledge workers in manufacturing have access to Microsoft Copilot and use it for better emails and meeting notes. Everything else is still mostly experimentation. While auditing PLC and SCADA logic on a recent project, Vlad expected the customer to insist on a hardened on premise model with a Dell IPC and dedicated GPUs. Instead, they shrugged and said put it in ChatGPT, the boilerplate logic has no real IP. Data governance on the carpeted side of the business is mature. On the OT side, it barely exists, and that gap matters as more plant floor data flows toward AI tools. For systems integrators, AI is compressing timelines on slow, repetitive work. Tag validation, electrical drawing automation, screenshot to bill of materials extraction, and functional spec to PLC starting points are all in active development. The tradeoff is that some of these tools save four weeks of manual auditing but require a couple of weeks to set up correctly, and a probabilistic LLM still demands human signoff on safety and control logic. Senior engineers benefit most because they already know what good output looks like. The bigger industry question is what happens to the junior to senior pipeline if entry level work disappears. Hardware tells a different story. Moore's Law, first proposed in 1965, held for about 60 years before chip density at three nanometers and heat budgets broke the cost curve. GPUs on the consumer side have been roughly stagnant since the Nvidia 30 series. On the industrial side, demand for radical hardware change has been low. PLCs, switches, IO modules, and field protocols look much like they did twenty years ago. IO Link, the protocol that should be a baseline for any Industry 4.0 deployment, was founded in 2006. Image recognition has unlocked pick and place applications that used to be too expensive to engineer the traditional way. The workforce thread runs underneath all of this. UPS recently negotiated voluntary buyouts of roughly one hundred and fifty thousand dollars per driver to remove tens of thousands of positions, while large technology firms continue to lay off staff and reinvest in data centers. Timestamps References About Your Hosts Want to go deeper? Vlad and the team at Joltek have covered related topics here: Dave Griffith is a co-host of The Manufacturing Hub Podcast and founder of Capelin Solutions, an industrial automation firm helping manufacturers adopt smart manufacturing technology. He brings 15 years of experience in industrial automation and digital transformation. | |||
| Ep. 256 - Why Machine Learning Still Outperforms LLMs for Manufacturing Process Control | 09 avr. 2026 | 01:09:37 | |
Digital twins and machine learning are redefining batch optimization in manufacturing. Learn how centerlining models can catch quality issues in real time before they become irreversible. Concepts like digital twins, golden batch profiles, and statistical process control have long promised more than they delivered. Virag Vora of Twin Thread argues that layering machine learning on top of these ideas is what finally brings them to life. In this context, a digital twin is entirely data centric: a real time and historical representation of a process that serves as the foundation for AI models. The core use case is batch centerlining. The model compares current conditions against historically successful profiles, segmented by raw material source, product type, and seasonality. An orange juice manufacturer uses Twin Thread to determine whether incoming fruit should be sold fresh or routed to concentrate based on seasonal sugar content. The model identifies contributing variables in real time and alerts operators before a batch drifts beyond recovery. Twin Thread tackles the "not enough data" objection head on. With over 60 connectors, the platform works with the fragmented data reality of most manufacturing sites. Even low frequency data can train a useful model that quantifies what higher resolution instrumentation would unlock. Virag draws a clear line between ML and LLMs for process control. ML models trained on historical data produce deterministic outputs trusted for real time guidance on machine settings. LLMs excel at document retrieval and natural language interaction but are not suited for recommending set points on a live line. Twin Thread layers both: ML handles optimization, while Twin Thread Advisor lets users interrogate data and configure models through conversation. The standout proof point is Hills Pet Nutrition. After three years on Twin Thread, their models automatically feed recommendations into live production. That closed loop followed a deliberate path from human validation to A/B trials to automated execution with operator opt out. About Virag Vora Virag Vora is a solutions professional at Twin Thread, a platform that combines data centric digital twins with machine learning to optimize manufacturing processes. With a background in chemical engineering, Virag began his career deploying MES and DCS systems in biotech and pharma before joining Tulip and then Twin Thread. He helps manufacturers connect their existing data infrastructure to AI powered optimization across batch, continuous, and hybrid processes. Timestamps 0:00 Introduction 1:20 Virag's background in chemical engineering and industrial software 6:30 Moving up the ISA 95 stack from DCS to MES and applications 9:00 How AI reinvents digital twin, golden batch, and SPC concepts 12:20 What a data centric digital twin actually looks like 21:40 Where digital twins deliver the most value in manufacturing 27:00 Seasonality, segmentation, and model training strategies 36:00 Data prerequisites for deploying industrial AI 41:40 Flavors of AI in manufacturing: ML, LLMs, and agentic workflows 50:40 Closed loop AI control at Hills Pet Nutrition 53:10 Personal project: Family Graph using knowledge graphs 56:20 Prediction: operators as human digital twins References Twin Thread: https://twinthread.com This episode is sponsored by MaintainX is an AI powered maintenance and operations platform that helps technicians get the answers they need instantly so they can focus on getting assets back online. Learn more about how MaintainX supports frontline manufacturing teams. https://maintainx.com About Your Hosts Vladimir Romanov is a co-host of The Manufacturing Hub Podcast and the founder of Joltek, an independent manufacturing and industrial automation consulting firm specializing in modernization strategy, digital transformation, and workforce development. Joltek works with manufacturers and investors to de-risk modernization and build the internal capability to sustain results. Connect with Vlad: https://www.linkedin.com/in/vladimirromanov/ Want to go deeper? Vlad and the team at Joltek have covered related topics here: Edge Computing, AI, and the Value of Manufacturing Data: https://www.joltek.com/blog/edge-computing-ai-value-manufacturing-data Digital Transformation in Manufacturing: https://www.joltek.com/blog/digital-transformation-in-manufacturing Dave Griffith is a co-host of The Manufacturing Hub Podcast and founder of Capelin Solutions, an industrial automation firm helping manufacturers adopt smart manufacturing technology. He brings 15 years of experience in industrial automation and digital transformation. Connect with Dave: https://www.linkedin.com/in/davegriffith23/ Subscribe to Manufacturing Hub: https://www.manufacturinghub.live LinkedIn: https://www.linkedin.com/company/manufacturing-hub-network | |||
| Ep. 255 - From Virtual Design to Physical AI: Vention's Blueprint for Industrial Robotics | 02 avr. 2026 | 01:04:21 | |
Physical AI is arriving on factory floors ahead of schedule, and Vention is already deploying it on applications four automation integrators failed to crack. François Giguère, CTO of Vention, draws a precise line between agentic AI and physical AI. Agentic systems process data and return data. Physical AI controls motion and actuation that produce real world consequences on a factory floor where a hundred percent uptime is the only acceptable standard. Giguère has spent a decade helping build Vention, a platform that lets manufacturers design robotic cells in 3D, program them through natural language, simulate them in a browser, and receive the physical machine shipped in modular components like an industrial kit. With a team of 95 engineers and three years as CTO, he brings a grounded perspective on where AI delivers real value in industrial automation and where it still falls short. The design, automate, simulate workflow at Vention represents one of the most complete implementations of AI-powered machine engineering currently in production. In the design phase, customers build systems from a modular component library. In the automate phase, an AI agent converts natural language prompts into Python control code for the entire cell including robot arms, conveyors, vision systems, and grippers. The program is validated in simulation before a single component ships. This is made possible by Vention's motion streaming architecture: instead of treating the robot as the master controller the way KUKA KRL does, Vention brings all motion planning, inverse kinematics, forward kinematics, blending, and trajectory optimization into its own software stack. The robot becomes a passive component consuming a motion stream, and the entire machine becomes programmable from a single unified codebase that AI tools excel at generating. Giguère notes that Vention's choice to use Python as the programming language for automation control gives their AI tools a measurable edge over environments built on structured text or ladder logic. Vention's two physical AI products are GRIP (Generalized Robotics Intelligence Pipeline) and Rapid AI Operator, a modular bin picking application built on top of GRIP. The technology relies on transformer-based foundation models. About François Giguère Timestamps This episode is sponsored by: About Your Hosts Want to go deeper? Vlad and the team at Joltek have covered related topics here: Dave Griffith is a co-host of The Manufacturing Hub Podcast and founder of Capelin Solutions, an industrial automation firm helping manufacturers adopt smart manufacturing technology. He brings 15 years of experience in industrial automation and digital transformation. Subscribe to Manufacturing Hub: https://www.manufacturinghub.live | |||
| Ep. 254 - From Cost Center to Growth Engine: The AI Future of Manufacturing Maintenance | 26 mars 2026 | 01:04:18 | |
AI in manufacturing is no longer a strategy reserved for the boardroom. It is a tool for the technician on the plant floor, and the results are already showing up in real operations worldwide. Most digital transformation strategies in manufacturing are built for desk workers on the carpeted side of the building, not the operators and technicians keeping production running on the concrete floor. AI platforms have historically been designed for white collar knowledge workers with time to navigate complex systems, leaving the frontline worker as an afterthought. Nick Haase recognized this gap when building MaintainX in 2018, and it became the foundational design principle behind everything the company built. The result is a platform now serving nearly 14,000 customers across manufacturing, food and beverage, facilities management, and any industry that depends on physical assets staying operational. The core thesis Nick brings to this conversation is that the person with no purchasing authority and no budget is the single most important factor in whether a digital transformation project succeeds or fails. That person is the frontline technician. Building for that user first required a mobile experience so intuitive that no training was needed, one that met workers in the flow of existing work rather than pulling them out of it. If your team needs a 300 page manual to use the platform, the adoption battle is already lost. The skilled labor shortage in manufacturing is not a forecast. The United States is projected to have more than 3 million manufacturing jobs unfilled by 2030, driven largely by retirement of experienced workers who have spent decades building institutional knowledge. That knowledge cannot be transferred through a job posting. MaintainX attacks this through AI powered voice note capture at work order closeout. Technicians leave a verbal description of what they found and fixed. The platform transcribes it across any language or accent, standardizes it, and builds a living knowledge base that outlasts the retirements of the people who created it. For organizations with similar equipment across dozens of sites, that knowledge becomes portable across locations and years. About Nick Haase Timestamps References This episode is sponsored by MaintainX About Your Hosts Dave Griffith is a co-host of The Manufacturing Hub Podcast and founder of Capelin Solutions, an industrial automation firm helping manufacturers adopt smart manufacturing technology. He brings 15 years of experience in industrial automation and digital transformation. Subscribe to Manufacturing Hub: https://www.manufacturinghub.live | |||
| Ep. 253 - How Manufacturers Can Turn Plant Data into AI Powered Insights w/ Konstantin Eukodyne | 19 mars 2026 | 01:28:15 | |
Industrial AI is getting a lot of attention in manufacturing right now, but one of the biggest questions is still the most practical one. How do you turn plant data, process knowledge, and operational constraints into something that actually creates value? In this episode of Manufacturing Hub, Vlad Romanov and Dave Griffith sit down with Konstantin Paradizov of Eukodyne for a detailed conversation on what industrial AI looks like when it is applied by people who understand manufacturing, MES, process improvement, data architecture, and the realities of the plant floor. What makes this discussion especially valuable is that it does not stay at the surface level. Konstantin shares how his background moved from pharma into food and beverage, how Lean Six Sigma and process thinking shaped his approach, and why many of the best opportunities in manufacturing still begin with understanding the actual workflow before talking about software. The conversation explores a theme that comes up again and again in industrial transformation: the biggest gains often do not come from adding more technology first. They come from understanding the problem clearly, identifying what information matters, validating assumptions with the people doing the work, and then using the right mix of tools to move faster. A major part of this episode focuses on the real use of AI in consulting and discovery. Konstantin explains how his team uses secure transcription workflows, on premises AI infrastructure, cloud models, masking of sensitive information, iterative validation, and ROI driven reporting to create high value outputs in a fraction of the time that would have been required even a year or two ago. This is an important point for manufacturers, system integrators, software teams, and plant leaders. AI is not just something that sits in front of an operator as a chatbot. It can be used behind the scenes to accelerate analysis, strengthen recommendations, shorten discovery, improve documentation, and reduce the cost of getting to a better answer. The technical section of this episode is especially strong for anyone working in industrial automation, OT data systems, or applied AI. The discussion covers on premises compute, Nvidia based edge hardware, Linux environments, Docker containers, RAG workflows, vector databases, knowledge graphs, MQTT pipelines, HiveMQ, Mosquitto, n8n, Claude Code, Cursor, Gemini, OpenRouter, and the tradeoffs between frontier models in the cloud and smaller or open models deployed closer to the process. One of the clearest takeaways is that manufacturers should not start with the biggest model or the most exciting headline. They should start with the problem, the constraints, the data path, and the economics of the solution. Vlad also pushes on an issue that matters to almost every manufacturer trying to prepare for AI. If you collect massive amounts of plant data into historians, cloud platforms, and enterprise systems, is that enough to create value later? Konstantin’s answer is thoughtful and realistic. More data alone does not automatically lead to better outcomes. You still need filtering, context, prioritization, architecture, and a disciplined way to separate signal from noise. Learn more about Joltek here:
Learn more about Eukodyne:
Timestamps References and resources mentioned in the episode
George Orwell 1984 George Orwell Animal Farm | |||
| Ep. 252 - Industrial AI in Manufacturing What Actually Works and What Does Not #industrialautomation | 12 mars 2026 | 01:05:39 | |
Manufacturing Hub is back with Episode 252, where co hosts Vlad Romanov and Dave Griffith break down what an AI survival guide should actually look like for manufacturing and industrial automation professionals. This is not a hype conversation about replacing people with magic software. It is a grounded discussion about what AI tools can do today, where they fail, why context and data quality matter so much, and how industrial teams should think about experimentation without losing sight of real operating constraints. In this episode, Vlad and Dave unpack the evolution many engineers and technical leaders have already felt in real time, from early prompt engineering, to agent based workflows, to MCP servers, skills, context management, and the growing cost of tokens and infrastructure. The conversation moves beyond generic AI commentary and into the reality of plant floor environments, where success depends on process knowledge, data architecture, OT constraints, cybersecurity, governance, and clear business value. One of the strongest themes throughout the episode is that manufacturers cannot skip the hard work of structuring data, understanding workflows, and defining use cases simply because AI tools are moving quickly. Vlad brings a very practical industrial lens to the discussion. Drawing on years of hands on experience across controls, manufacturing systems, plant modernization, and digital transformation, he explains why industrial AI has to start with operational context. A maintenance team, an engineering team, and a quality team do not need the same data, do not ask the same questions, and should not be handed the same AI workflows. That distinction matters. This conversation also highlights why the best industrial AI implementations will likely come from teams that combine domain expertise with strong technical execution, rather than generic AI shops trying to force a solution into environments they do not fully understand. Dave adds an important systems and adoption perspective, especially around cost, scaling, management expectations, and the danger of trying to prompt your way past foundational architecture work. Together, Vlad and Dave explore why manufacturers are interested in AI, why many are afraid of being left behind, and why so many projects still stall once they hit the realities of obsolete equipment, weak data models, fragmented systems, and unclear ownership of information. They also discuss deterministic logic versus LLM behavior, reporting workflows, industrial dashboards, PLC code generation concerns, and the practical question every manufacturer should ask before investing: what problem are we solving, for whom, and what is the measurable return? For those new to Vlad, he is an electrical engineer and manufacturing leader with deep experience across industrial automation, controls, data systems, OT architecture, modernization strategy, and plant operations. Through Joltek, Vlad works with manufacturers on digital transformation, IT OT architecture and integration, modernization planning, operational improvement, and technical workforce enablement. Learn more here: If you are a plant leader, controls engineer, systems integrator, OT architect, SCADA or MES practitioner, or simply someone trying to separate useful AI workflows from noise, this episode will give you a much more realistic framework for thinking about industrial AI adoption. Timestamps | |||
| Ep. 251 - Ignition 8.3 ProveIt How Inductive Automation Scales Multi Site Factories w/ MQTT and UNS | 05 mars 2026 | 01:03:12 | |
In this episode of Manufacturing Hub, Vlad and Dave sit down with Travis Cox and Kevin McCluskey from Inductive Automation to unpack what was actually proven at ProveIt and why it matters for teams trying to modernize plants without building a fragile mess of point to point integrations. If you have ever looked at a shiny demo and wondered what the real architecture looks like, how it scales beyond a single line, and what it takes to roll out across multiple sites without turning every change into a high risk event, this conversation is for you. Travis and Kevin walk through their ProveIt Enterprise B build and the thinking behind it. The core idea is simple but powerful: treat the factory like a system that needs a shared digital infrastructure, built on open standards, where data is contextualized and reusable. They break down how they used Ignition Edge close to PLCs for resiliency, local HMIs, and disciplined data modeling, then moved data through MQTT into a Unified Namespace so multiple applications can consume the same trusted signals and context. This is the difference between “we can connect to anything” and “we can scale without rewriting everything every time the business changes.” Open standards show up repeatedly in the conversation because ProveIt is specifically designed to force interoperability and practical implementation tradeoffs. Inductive Automation has also written about ProveIt as a place where MQTT, OPC UA, and SQL show up as real foundations rather than slogans. From there, the episode gets into the part that should make both OT and IT teams pay attention: modern deployment practices applied to industrial applications. Kevin outlines a clear maturity path from a single designer workflow to version control, then to containerized deployments, and finally to full GitOps style promotion across dev, staging, and production using tools like Argo CD, Helm, Kubernetes, and release promotion concepts that look like what the software world has used for years. Argo CD is explicitly built around Git repositories as the source of truth for desired state, which is exactly why it fits this style of deployment. The live portion of the conversation demonstrates how fast this can get when the infrastructure is treated as code: they spin up a brand new “site four” by submitting a form, generating a pull request, merging it, and letting the pipeline do the rest. Timestamps About the hosts Dave Griffith co hosts Manufacturing Hub and brings a practitioner lens focused on what works on the plant floor, how architectures survive real constraints, and how industrial teams can modernize without breaking production. About the guests Learn more about Joltek | |||
| Ep. 246 A - Factory of the Future Without the Hype: Siemens on Data Transparency, Orchestration, and Trust in AI | 12 févr. 2026 | 00:59:10 | |
This episode wraps up our Technology Modernization theme with a Siemens perspective that feels very grounded in what factories are actually dealing with right now. Brian Albrecht and Louis Hughes from the Siemens XD team walk through what they are seeing in the field across brownfield and greenfield conversations, why executives keep asking for industrial AI before the foundations are ready, and what it really takes to turn messy plant data into something you can trust for analytics, operations, and eventually AI enabled workflows. A big thread in this conversation is that modern manufacturing is not blocked by ambition, it is blocked by readiness. Everyone wants faster decisions, fewer surprises, and higher uptime, but the path there usually starts with boring work that is not optional. Data transparency across machine, plant, MES, and cloud layers. A clear definition of what real time actually needs to mean for a given use case. And a plan to contextualize and orchestrate data so that AI does not get fed junk inputs. Brian and Louis explain how they approach those early customer conversations, how workshops turn vision into prioritized use cases, and why trust, pilots, and repeatability matter more than flashy demos when you are working in regulated or high consequence environments. If you have been hearing nonstop AI buzz but you are still wrestling with legacy controls, inconsistent tags, documentation that no one can find, and seven layers of security constraints, this episode is for you. We get into practical use cases like AI vision and anomaly detection, LLMs for tribal knowledge and troubleshooting workflows, and the idea of fast versus slow AI, meaning AI that must act during production versus AI that can analyze after the fact. Timestamps About the hosts Dave Griffith is the cohost of Manufacturing Hub and an industrial automation practitioner who focuses on how modern technologies translate into real factory outcomes, from controls and data foundations to scalable implementation strategies. About the guests
Referenced in the episode Crossing the Chasm by Geoffrey A Moore Extreme Ownership by Jocko Willink and Leif Babin | |||
| Ep. 246 - Building a Life Sciences Virtual Factory Enterprise C, MQTT, and UNS w/ Amy Williams | 06 févr. 2026 | 01:04:48 | |
In this special ProveIt edition of Manufacturing Hub, Vlad Romanoff and Dave Griffith sit down with Amy Williams from Skellig Automation to unpack Enterprise C, a life sciences virtual factory built to look and feel like the reality inside many regulated facilities today. If you work around batch processes, compliance, historian projects, electronic batch records, or industrial data architecture, this conversation is a practical walkthrough of what it actually takes to turn raw signals into a story you can defend, improve, and scale. Amy has spent years working exclusively in life sciences manufacturing, starting deep in DeltaV automation for batch pharma and moving into digital transformation projects that focus on open architectures, modern data pipelines, and real operational outcomes. In this episode, she explains what Enterprise C is simulating, why it was designed as an Industry 3.0 style biotech startup, and what kind of data and documentation a vendor would have to wrestle with in the real world. The factory is producing a fictional enzyme using a fed batch fermentation process, and the UNS publishes realistic one second resolution batch data across four pieces of single use equipment including a mixer, a bioreactor, a chromatography skid, and a TFF skid. One of the most valuable parts of this episode is the reminder that data sitting in an MQTT broker is not inherently valuable. The value comes when the data is contextualized enough that different teams can use it without tribal knowledge, and when the resulting traceability helps you answer the questions that matter in life sciences. What happened during the batch, what changed compared to previous runs, what went out of spec, what documentation proves compliance, and what you should do next time to avoid losing a batch that can cost millions. Amy also explains why Enterprise C intentionally includes uncontextualized tags and paper files, because that is exactly where many facilities still are. The hard part is not connecting a sensor, the hard part is governance, agreement, and building a model that humans actually follow. You will also hear the crew dig into Smart Manufacturing Profiles and why standardizing information models is one of the clearest paths toward true interoperability. If you are tired of every site, every integrator, and every project reinventing the same pump, valve, and equipment model from scratch, this is the kind of conversation that helps frame why that problem keeps repeating and what might finally reduce it. The ProveIt format forces the questions that most conferences avoid, including what problem was solved, how it was done, how long it took, and what it cost. That is exactly why this conference has become a magnet for practitioners who care about the difference between a demo and a deployable solution. About the hosts About the guest Timestamps References and links mentioned ProveIt Conference CESMII Smart Manufacturing Profiles and Marketplace Joltek resources related to this episode
Subscribe and follow Manufacturing Hub for more conversations on technology modernization, UNS architecture, MQTT, industrial data systems, and how real factories actually evolve when the goal is uptime, compliance, and measurable outcomes. | |||
| Ep. 245 - Modernizing Manufacturing | Data, OEE, Quality Analytics - Everyone Wants the Same Signals | 05 févr. 2026 | 01:00:30 | |
In this episode of Manufacturing Hub, Vlad Romanov and Dave Griffith sit down with David for a practical, operator grounded conversation about industrial data, modernization, and what it actually takes to turn plant floor signals into business decisions. David has spent more than two decades in manufacturing across automotive, solar, and electric vehicles, and his story is a familiar one for a lot of us. He walked into a plant thinking he was there for a project, discovered PLCs in real time, and never left the factory world. From early days wiring up a SQL Server to pull line data instead of sending people out with stopwatches, to leading data and analytics and shaping MES and reporting strategy, this conversation stays focused on the messy middle where most factories live. A big theme here is that collecting data is not the same thing as creating information. As tooling has improved, connectivity, historians, SCADA, cloud storage, MQTT, and the modern ecosystem have made it easier to get signals out of machines. The hard part is deciding what matters, aligning stakeholders, and creating context that survives across teams and projects. David breaks down how real progress often starts with simple visibility, what is ruining your day, what is the biggest safety risk, what is the recurring quality miss, what is the downtime story you do not trust, then builds from there using workshops and iterative delivery instead of giant multi year “boil the ocean” programs. We also get into Unified Namespace, why it resonates with people who have been burned by tightly coupled ISA style integrations, and why change management is the hidden cost. If you are exploring UNS, this episode highlights the difference between drawing the box on a whiteboard and getting a whole organization to actually adopt consistent naming, context, and ownership. Then we finish with a grounded take on industrial AI. No hype, no doom. Just a realistic view of where AI helps today, where it breaks, and why context windows, documentation quality, and domain expertise still decide whether results are useful or dangerous. Timestamps About the hosts Dave Griffith is the co host of Manufacturing Hub and works at the intersection of manufacturing operations, technology modernization, and practical delivery. He focuses on helping teams bridge the gap between “we want data” and “we can run this plant better next quarter.” About the guest Links from Joltek
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| Ep. 244 - How Modern Plants Actually Bridge Legacy Automation and AI w/ Benson Hougland | 29 janv. 2026 | 01:08:18 | |
In this episode of Manufacturing Hub, Vlad Romanov and Dave Griffith sit down with Benson Hougland from Opto 22 to get brutally practical about what is actually running on shop floors today, and what it takes to move from legacy automation to modern, data ready operations without breaking what already works. If you have ever walked into a plant and seen a mix of decades old controllers, manual processes, islands of automation, and a few shiny modern pockets of connectivity, this conversation will feel very familiar. Benson has spent roughly three decades at Opto 22 and he has seen the full spectrum, from brownfield realities where nothing can go down, to greenfield expansions where teams can finally design with data, security, and integration in mind. A major thread in this discussion is the gap between “the machine runs” and “the business can learn from the machine.” Benson lays out why so many facilities still operate in a world of siloed equipment with minimal visibility, and why digital transformation stalls when the goal is vague or driven by trend chasing. The most actionable insight is simple: start with a real problem, win small, build trust in the data, and only then scale. That approach is how you avoid proof of concept purgatory, and it is also how you get leadership buy in without overpromising. If you are looking at industrial AI, it becomes even more critical, because manufacturing cannot tolerate hallucinated answers. Benson explains why industrial AI starts with sanctity of data, meaning clean, contextualized, trustworthy signals that an organization can actually act on. You will also hear a grounded take on why hardware still matters in 2026. Not because everyone wants to rip and replace working PLCs, but because modern plants need layered edge strategies that can extract the right data, protect legacy assets, and integrate upward using open methods. About the guest About the hosts Dave Griffith is a long time manufacturing and automation practitioner focused on bridging the gap between modern technology conversations and what is practical on the plant floor. Dave brings a systems mindset to modernization, with a strong emphasis on outcomes, maintainability, and the human factors that decide whether projects scale or stall. If this episode resonates and you are navigating modernization decisions, especially around OT networking, data infrastructure, platform selection, or plant floor security, Joltek can help you evaluate your current state, define a realistic target architecture, and build a roadmap that your team can execute. Joltek links | |||
| Ep. 243 - From Legacy Systems to AI Readiness A Realistic Look at Manufacturing Modernization | 22 janv. 2026 | 01:01:32 | |
Technology modernization in manufacturing is not a list of shiny tools. It is a sequencing problem. In this episode of Manufacturing Hub, Vlad Romanov and Dave Griffith break down why the executive vision for AI often collides with the reality of the plant floor, and what a practical path forward actually looks like when you account for data quality, legacy controls, networking, and the true cost of integration. A core theme in this conversation is imperfect information. Leaders often believe the data already exists because reports exist. But a stack of paper, a few spreadsheets, or a single counter value is not the same as contextualized, trustworthy history that can drive decisions or support advanced analytics. Vlad and Dave walk through why foundational work matters, what teams usually miss during modernization, and how quickly the bill grows when you discover your architecture is outdated, undocumented, or full of dependencies you cannot see until you open panels and start tracing signals. You will also hear a grounded debate on how to think about SCADA, MES, historians, dashboards, and what it would actually mean to “feed data into AI” in a manufacturing context. The takeaway is simple. If you want better outcomes, you need a better understanding of your current state, a clear business case, and a roadmap that prioritizes what matters operationally. Modernization is not one big upgrade. It is a series of decisions that either reduce friction or create it. About the hosts Learn more about Joltek Dave Griffith is an industrial automation practitioner and consultant who works closely with manufacturers to modernize legacy environments, improve reliability, and build practical systems that operators and maintenance teams can support. Dave brings a strong perspective on what is feasible in real plants, where uptime, risk, budget, and organizational readiness drive every decision. Timestamps References and links mentioned Manufacturing Hub Podcast ProveIt Conference Automate Show Ignition Community Conference If you are watching on YouTube, subscribe so you do not miss the rest of this month’s deep dives on hardware, data teams, and practical applications that actually work on real plant floors. | |||
| Ep. 242 - From Controls to MES Building Manufacturing Systems That Scale Without Breaking Operations | 15 janv. 2026 | 00:58:47 | |
In this episode of Manufacturing Hub, hosts Vlad Romanov and Dave Griffith welcome back Amos Purdy for a wide ranging conversation that connects plant floor reality with SCADA, MES, and the business decisions that actually fund modernization. Amos shares his path from early software and programming work into industrial automation, including building an industrial automation class and lab, leading MES and SCADA efforts, and working across industries where the pace, constraints, and validation expectations can feel like completely different worlds. If you have ever wondered why a solution that looks obvious on a whiteboard takes months or years to land on a production line, this episode breaks down the human, technical, and financial reasons in plain terms. A big thread throughout the conversation is what it takes to build systems that last. The group digs into hiring and mentoring for Ignition based teams, what backgrounds translate well, and why “hobbyist energy” can be a real superpower in interviews and on the job. The practical takeaway is simple: credentials help you get in the door, but projects help you stand out, especially when you can explain the problem, the architecture, and the tradeoffs you made. The conversation also gets real about legacy plants, where the constraint is often not ambition but risk, ROI, and operational disruption. The group frames modernization as a sequence of targeted moves that improve data availability, reduce cybersecurity exposure, and create a foundation for future applications without betting the entire facility on a massive rip and replace. You will also hear a grounded take on AI in industrial settings. The panel separates what is useful today from what is still hype, and explains why industrial AI needs context, standards, and purpose built training data to be trusted. They connect that to the “data transparency” problem: companies want answers faster, but the hard part is making the data accessible, reliable, and safe in the first place. The episode closes with a discussion on EV and battery manufacturing trends, the reality of global standards and certification, and what the next few years could look like as edge devices, connectivity, and power systems evolve. Hosts Dave Griffith Guest Timestamps References and links mentioned Ignition SCADA overview Inductive University training ProveIt Conference 2026 details Edison Motors 2030: How Today’s Biggest Trends Will Collide and Reshape the Future of Everything by Mauro F. Guillén https://www.joltek.com/services | |||
| Ep. 241 - Manufacturing in 2026 AI Reality Cybersecurity Data Careers and What Comes Next | 08 janv. 2026 | 01:14:31 | |
Welcome to Manufacturing Hub and welcome to 2026. In this kickoff episode, Vlad Romanov and Dave Griffith reset the table for the year and share what the show is really about: practical conversations with people who build, run, secure, and modernize manufacturing systems. If you are new here, this is the perfect starting point because we explain the format, the monthly themes, and the reason we keep coming back to the same hard truth: manufacturing improvement is never just about technology. It is also about people, process, incentives, and change. From there, we get into the big question everyone is asking right now: what actually changes in 2026 for manufacturing and industrial automation. We talk about why AI stopped being a novelty and started becoming a permanent part of the landscape, and we separate the hype from the applications that are starting to look real. We discuss where AI helps today, where it still struggles, and why most teams will not get value until they build stronger fundamentals in data collection, context, and operational ownership. We also connect the dots between AI and the pressure it puts on infrastructure, security posture, and decision making, especially when the plant floor reality is still paper logs, tribal knowledge, and inconsistent system documentation. We also cover what we expect to see across the core pillars of the industrial stack: plant floor data and operations, engineering and commissioning workflows, back office analytics, OT cybersecurity, industrial data platforms, and how the systems integration market is evolving as more work moves upward into analytics, architecture, and long term modernization programs. Finally, we zoom out into careers, acquisitions, private equity activity, and what these shifts mean for engineers, leaders, and teams trying to build durable capability instead of chasing the next shiny tool. If you are planning your year, come meet us in person. We will be at ProveIt in Dallas, Texas February 16 to 20. We will also be at Automate in Chicago, Illinois June 22 to 26. And we are expecting to be back at the Ignition Community Conference in Sacramento, California September 22 to 26. Timestamps 00:00 Welcome to 2026 and why we are back Hosts Vlad Romanov is an electrical engineer and manufacturing consultant focused on industrial automation, modernization, OT data, and IT OT alignment. He runs Joltek and builds educational content for engineers and technical leaders. Dave Griffith has 17 plus years in industrial automation and manufacturing and leads Kaplan Solutions, focused on operational excellence, data systems, and delivering projects that make plant performance visible and actionable. References mentioned How to tackle the AI skills gap, Boston Consulting Group What’s Next for AI in 2026, MIT Technology Review Getting Naked, Patrick Lencioni | |||
| Ep. 236 - How to Deliver Manufacturing Projects That Operations Actually Use | 04 déc. 2025 | 01:31:14 | |
Handing over a project is one of the most underestimated and misunderstood phases in manufacturing and industrial automation. In this episode of Manufacturing Hub, Vlad and Dave sit down to break apart real stories from the field covering MES rollouts, line commissioning, SCADA and ignition development, operational adoption, and the very real consequences of poor knowledge transfer. Most conversations online focus on the technical build, but very few people emphasize the point where engineering lets go and the operations team becomes the true owner of the system. This episode brings forward examples of both well executed handovers and catastrophic failures that every engineer, integrator, or manager can learn from. Vlad begins by walking through his experience building MES and data collection systems for food and beverage facilities where each plant had different architectures, legacy systems, undocumented networks, and obsolete PLCs. These initiatives required deep assessments, phased modernization, server deployments, KPI development, and the long journey from data collection to actual operational use. The most important insight is that success rarely comes from the technology alone. It comes from the extent to which operators, supervisors, and CI teams are trained, empowered, and aligned to use what has been built. Dave then shares a story from a multi year track and trace project that technically worked but failed at the operational handover stage because the one scheduler refused to schedule inside the system. The entire project was mothballed despite millions of dollars invested. The lesson is simple. Technology cannot compensate for missing stakeholder alignment and poor discovery. Human influence can halt even the most well engineered solution. Timestamps Hosts Dave Griffith References Mentioned in the Episode | |||
| Ep. 235 - How to Build and Run a Systems Integration Company in Manufacturing | 20 nov. 2025 | 01:23:16 | |
This episode takes you inside the reality of becoming a systems integrator and growing a technical services business from the ground up. Vlad and Dave share their personal experiences launching and running integration companies, the lessons they learned as engineers moving into business ownership, and the challenges that come with finding customers, choosing technologies, setting rates, managing cashflow, and hiring the right people. This is a detailed and candid look at what the journey actually requires. It is also a practical conversation that breaks down how technical professionals can evolve beyond pure engineering work in order to build a sustainable integration practice in the world of manufacturing and industrial automation. The episode begins by grounding the definition of a systems integrator in the context of modern industrial environments. Vlad and Dave explore the many different shapes and levels of integrators across the ISA eighty five and ISA ninety five landscape, from controls and PLC programming to SCADA development, MES implementations, and specialized software delivery. They also explain why customers hire integrators, why the most valuable asset is always the people, and why the hardest part of the work is rarely technical. Vlad shares insights from his decade in engineering and operations roles at Procter and Gamble, Kraft Heinz, and Post Holdings, followed by senior engineering and management positions at multiple systems integration firms. Dave brings his experience from aerospace, OEM machine building, distribution, and running his own integration business focused on manufacturing execution systems and ignition development. The conversation then shifts to the earliest stages of starting an integration company. Vlad and Dave describe the moment when most professionals decide to go out on their own, which usually begins with feeling constrained by corporate structures or wanting more autonomy over the projects they work on. They break down the difference between being a contractor and building a long term business and why many technical founders underestimate the reality of sales, marketing, legal administration, cashflow management, and relationship building. The discussion highlights how timing and relationships drive early opportunities far more than technical ability and why every contract carries its own risk profile that needs to be negotiated with care. Listeners are then guided through the real startup requirements for a systems integration company. This includes liability insurance, business registration, accounting and bookkeeping tools, mileage and expense tracking, choosing an internal technology stack, managing licenses, and understanding when to invest in programming software or rely on customer owned licenses. Vlad and Dave explain the role of net thirty, net ninety, and even net one hundred eighty payment terms and why long payment cycles can destroy cashflow if not anticipated correctly. They also share practical frameworks for setting hourly rates, pricing time and materials versus fixed projects, and calculating the true cost of travel, administration, and sales time that erode billable hours. Timestamps Systems integrators article Manufacturing consulting insights Digital transformation in manufacturing Industrial cybersecurity fundamentals | |||
| Ep. 234 - What Students Learn When They Build Ignition Projects in Seventy Two Hours | 13 nov. 2025 | 00:30:54 | |
In this conversation recorded at the Ignition Community Conference, Vlad, Dave, and their guest David Grussenmeyer from Inductive Automation explore one of the most important and inspiring stories in the world of industrial automation education. David leads the Educational Engagement Program at Inductive Automation and has spent the last several years building a global network of universities, colleges, students, and integrators who are working together to bridge the gap between academic theory and real world industrial skills. This episode provides a detailed look at how the Student Buildathon was created, how it works, why it matters, and what it means for the future of the controls and automation workforce. The discussion goes far beyond the event itself. David explains how the industry’s needs for engineering talent have shifted, why many academic institutions struggle to keep pace with modern automation technologies, and how Inductive Automation is supporting both professors and students to meaningfully upgrade the curriculum. The episode also explores the importance of industry partnerships, the challenge of faculty bandwidth, the value of internships and academic co op programs, and the realities of teaching automation in an evolving landscape of legacy systems, modern platforms, and everything in between. Listeners will gain insight into how universities can adopt Ignition, how integrators can help shape the workforce pipeline, how students can develop real industry skills before graduating, and how modern industrial technology can be taught effectively without overwhelming educators. Vlad and Dave also share their own perspectives from years of integration work and reflect on how different their own educational experiences would have been if programs like this had existed earlier. This episode is educational, practical, and inspiring for anyone working in automation, industrial education, system integration, or workforce development. Timestamps Vlad Romanov Dave Griffith David Grussenmeyer Educational inquiries can be sent to edengagement@inductiveautomation.com Referenced Resources from the Episode Inductive Automation Educational Engagement Program Inductive University | |||
| Ep. 233 - From Controls to Full-Scale Robotics Integration How Bright IA Leads in Automation | 30 oct. 2025 | 01:18:25 | |
In this episode of Manufacturing Hub, hosts Vladimir Romanov and Dave Griffith sit down with Davide (David) Pascucci, founder of Bright IA (https://brightiatx.com/), for an in-depth conversation about what it truly takes to build, grow, and succeed in the world of robotics integration and industrial automation. Davide shares his incredible journey from Italy’s oil and gas sector to leading one of Texas’s most promising automation firms. His story highlights the reality of moving from traditional controls work to full-scale robotics integration. Listeners will learn how his company evolved from small local projects into complex manufacturing solutions involving welding cells, painting robots, and palletizing systems used across multiple industries including food and beverage, fabrication, and renewables. The discussion explores how system integrators can strategically position themselves in the modern automation ecosystem. Davide explains the importance of vendor relationships, revealing how open collaboration with companies like Fanuc and KUKA helped his firm grow while avoiding common pitfalls faced by new integrators. He provides practical insights into how to evaluate robot brands, manage the mechanical design and safety aspects of projects, and find the right balance between in-house engineering and subcontracting work. Listeners will also hear a detailed perspective on the Texas manufacturing landscape, where oil and gas still dominate but are now accompanied by a new wave of innovation from defense, aerospace, semiconductor, and AI-driven industries. Davide explains how these shifts are creating a demand for flexible automation and robotics expertise across the region. A large portion of the conversation focuses on the real-world challenges that come with integrating robots on the factory floor. Davide talks about dealing with customers who insist on collaborative robots when industrial robots are better suited for the job. He describes how simulation and digital twin tools can help demonstrate cycle times and prove system capabilities before implementation. His transparency about pricing, quoting, and project management makes this a must-listen episode for anyone looking to understand the business side of integration, not just the technical aspects. The episode also explores how smaller robotics firms can collaborate with European and Asian OEMs that are entering the North American market. Davide shares the lessons he learned when working with foreign manufacturers, emphasizing that support, spare parts, and local presence are often more valuable than price alone. His advice is invaluable for early-stage integrators trying to evaluate new partnerships or decide which technologies to adopt. As the conversation continues, Davide, Vlad, and Dave discuss what the future holds for robotics integration. Davide predicts an explosion of applications over the next few years, driven by manufacturing reshoring, labor shortages, and advancements in AI and simulation. He believes that companies who fail to automate will simply be left behind. His message to manufacturers is clear: whether you like it or not, automation will be necessary to stay competitive. Listeners will also appreciate Davide’s insights into workforce development and training. He believes that plant operators and technicians must reskill to remain relevant in a world where machines are becoming smarter and more autonomous. He shares inspiring stories of training shop floor workers to operate robots with confidence and how empowering end users ultimately makes integration projects more successful and sustainable. Toward the end of the episode, the group reflects on what it means to build a modern systems integration business. Davide shares lessons on quoting, scaling a team, developing repeatable processes, and thinking strategically about products versus projects. His perspective highlights the difference between being a contractor and building a true business that can scale and create long-term value. Finally, the conversation closes with book recommendations that have shaped Davide’s thinking, including Extreme Ownership by Jocko Willink, Buy Back Your Time by Dan Martell, and of course, the timeless lessons found in The Bible. These selections capture the mindset of a leader who believes in responsibility, efficiency, and personal growth. If you are an engineer, systems integrator, plant manager, or decision-maker in manufacturing, this episode will give you a firsthand look into the future of robotics integration. It will help you understand how to evaluate partners, manage projects, and prepare your organization for the next generation of automation. Timestamps 00:00 Introduction and overview of the Systems Integrator theme
Bright IA is an automation and robotics integration firm based in Texas, providing complete engineering solutions for manufacturing environments, including welding systems, palletizing, safety integration, and industrial control design.
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| Ep. 232 - Future of Automation with Siemens: Industrial AI, Virtual PLCs, and Digital Twin Factories | 23 oct. 2025 | 01:48:04 | |
At Automate 2025, Vlad and Dave take Manufacturing Hub inside the Siemens booth to explore how one of the world’s largest industrial technology companies is shaping the future of manufacturing. From the latest S7-1200 G2 PLC to industrial copilots powered by AI, digital twins that simulate entire factories, and virtual PLCs redefining automation, this episode is packed with insights from Siemens leaders and engineers. In this conversation series, we uncover the evolution of hardware, software, and data-driven manufacturing with experts including Chris Stevens and Anna-Marie Breu on customer experience and digital twins, Bernd Raithel on software-defined automation and IT/OT convergence, Louis Narvaez on the next-generation S7-1200 G2 PLC, Kristen Sanderson on Industrial Copilot and AI agents, Sarah McGee on Sematic AX and modern PLC programming, Kevin Wu on Pick AI Pro, Ivan Hernandez on the G220 drives, and cybersecurity specialists Tilo and Gaurav on securing industrial networks. Throughout the episode, Vlad and Dave discuss how Siemens is transforming plant operations through tools that connect the physical and digital worlds. Topics include co-pilots for engineering and operations, lifecycle management, virtual commissioning, edge computing, harmonics and clean power, and the convergence of IT and OT teams. This conversation is a must-watch for engineers, integrators, plant managers, and decision-makers looking to understand how software-defined automation, AI, and digital twin technologies are merging to create resilient, data-driven factories. Timestamps: References Mentioned:
About the Hosts: Dave Griffith is a manufacturing consultant and co-host of the Manufacturing Hub podcast, helping manufacturers navigate digital transformation, technology adoption, and operational excellence. | |||
| Ep. 222 - Pick AI Pro with Kevin Wu | Faster Picking, Higher Reliability, Digital Twin and Vision AI | 16 oct. 2025 | 00:16:40 | |
Modern robotic picking is moving beyond neat rows and perfect lighting conditions. In this Automate 2025 conversation, Vlad and Dave sit down with Kevin Wu from Siemens to explore how Simatic Robot Pick AI Pro is tackling the messy reality of warehouses and factories. They discuss how the new edge architecture with the Simatic IPC BX 59 A and an NVIDIA GPU lifts pick rates to well over one thousand picks per hour, why multiple suction patterns matter for stability on large or flexible items, how camera agnostic support opens the door to new vision hardware, and why transparent objects are no longer a limitation in many applications. This episode also dives into digital thread and digital twin workflows using Siemens Process Simulate. These tools allow teams to test new products and layouts virtually before any hardware changes are made, helping reduce commissioning risk and shorten the path to production. The discussion highlights an on-booth demonstration that combines a robot with a secondary camera and a vision language model to identify products and read packaging details such as expiration dates. It is a clear example of how multimodal AI can complement traditional industrial vision systems. A major theme throughout this conversation is resilience. In real operations, products are rarely placed perfectly. Pallets shift, orientations vary, and lighting changes throughout the day. Traditional rules-based vision systems often struggle when small variances accumulate. Kevin explains how model-free 3D picking localizes unknown objects in clutter, selects stable suction patterns based on measured dimensions, and keeps production moving without forcing operators to maintain perfect alignment. For manufacturers in consumer packaged goods and medical devices, this is a meaningful advancement. It enables greater product variety and frequent SKU changes while maintaining engineering control. The difference is that the picking logic adapts to what the system sees rather than expecting the environment to remain static. We also talk about practical evaluation and proof of concept. Siemens runs application testing at its Berkeley, California lab where customers can send sample parts for quick feasibility checks. A short video of their parts being picked can provide the confidence needed to move forward with a pilot project while minimizing cost and risk. For quality inspection and defect detection, Siemens also offers an Inspector station capable of learning from as few as twenty samples to identify defects in real time. The discussion closes by looking at the future of digital manufacturing. Digital thread tools make it possible to simulate robots from multiple brands, test new configurations, and evaluate throughput virtually. Combined with edge AI and NVIDIA vision language technology, this creates faster experimentation cycles, improved reliability, and measurable gains in uptime and throughput. Kevin’s key message is clear. Manufacturers do not need to replace existing automation to explore the benefits of AI. Start with one process, validate performance, and build from there. Timestamps References and Resources Mentioned Siemens Press Release on Simatic Robot Pick AI Pro Siemens Simatic IPC BX 59 A Industrial Edge Device with NVIDIA GPU Siemens IPC BX 59 A Operating Instructions Universal Robots Example with Simatic Robot Pick AI Zivid Transparent Object Imaging Information https://blog.zivid.com/zivid-omni-engine Siemens Digital Thread Overview and Tecnomatix Process Simulate https://plm.sw.siemens.com/en-US/tecnomatix/ NVIDIA Vision Language Model Resources Hosts Dave Griffith is a manufacturing consultant and long-time co-host of Manufacturing Hub. He helps teams align operations, engineering, and leadership around the projects that move the needle in real production environments.
https://www.sw.siemens.com | |||
| Ep. 231 - Travis Cox on Ignition 8.3 | ICC 2025 Highlights and the Future of Industrial Software | 09 oct. 2025 | 00:51:00 | |
ICC 2025 was a clear level up for the Ignition community. In this conversation Vlad and Dave share on the ground insights from a week of packed sessions, vendor showcases, and ProveIt demonstrations that brought working integrations to life. They unpack why the move to a larger venue created more chances for deep technical conversations, how the community benefited from hands on demos that connected to a shared data backbone, and what record attendance means for the growth of modern SCADA and manufacturing data platforms. The episode then shifts into a focused discussion with Travis Cox from Inductive Automation on the launch of Ignition 8.3 and what it unlocks for builders who care about reliability, scale, and speed. We discuss how 8.3’s configuration in the file system and the expanded REST API enable real version control and DevOps workflows in day to day projects. We explore practical AI opportunities through MCP servers that can safely expose context and operational data to large language models, with an emphasis on operator augmentation, faster troubleshooting, and responsible guardrails. We connect the dots between OT networking fundamentals and secure architectures by highlighting the growing need for segmentation, deterministic traffic, and resilient data movement. Throughout the episode we keep the focus on what matters in plants today clear outcomes for uptime, quality, and delivery rather than hype. Whether you are an engineer, integrator, or an operations leader, this episode gives you an actionable snapshot of where Ignition and the broader ecosystem are heading. You will hear what the community is building, which 8.3 features are worth testing first, how ProveIt style showcases help end users evaluate technologies, and why investing in networking skills remains one of the highest ROI moves for manufacturers. Timestamps About the hosts Guest Episode references and resources Control Global highlights from ICC 2025 https://www.controlglobal.com/industry-news/news/55321625/highlights-from-inductive-automations-2025-icc-build-a-thon-and-award-winners ProveIt Conference official site https://www.proveitconference.com ProveIt at ICC background https://inductiveautomation.com/blog/proveit-showcases-are-coming-to-icc-2025 Books and learning mentioned or implied in the discussion Ignition 8.3 videos and feature overviews https://www.youtube.com/watch?v=Qds7RI9-hxg Connect with Manufacturing Hub Spotify https://open.spotify.com/show/1gE6glbxdYIfG6KUeOCz22 Call to action | |||
| Ep. 230 - AI in Manufacturing with Tom Hechtman of Sepasoft | Real ROI, MES on Ignition, Sepa IQ | 25 sept. 2025 | 01:11:57 | |
Artificial intelligence is no longer just a buzzword in manufacturing. The pace of adoption has been incredible, yet the reality is far more complex than flashy headlines suggest. In this episode of Manufacturing Hub, Vlad Romanov and Dave Griffith welcome back Tom Hechtman, founder of Sepasoft, to explore how AI is actually being deployed on the plant floor, what barriers remain, and whether we are truly transforming manufacturing or simply tinkering at the edges. Tom brings decades of experience building MES solutions for manufacturers around the globe. From his early days in the Midwest working with Rockwell Automation technology to launching Sepasoft’s Ignition MES modules and now leading the development of Sepa IQ, Tom has been at the forefront of data, analytics, and system integration. His insights bridge the gap between hype and practice, helping us understand where AI creates real ROI, where it still falls short, and how to build the foundations for success. Throughout the conversation we dive into the challenges of quality improvement, predictive maintenance, scheduling optimization, and contextualizing plant data. We discuss the importance of trust in both data and AI-generated outputs, the economics of running LLMs and machine learning models, and why cybersecurity and data governance cannot be an afterthought. Drawing on the recent MIT study that revealed only 5 percent of AI projects make a measurable P&L impact, Tom helps us unpack what manufacturers need to do differently if they want to avoid being part of the 95 percent that fail. We also get an update on Sepa IQ and how customers are using it to connect plant floor data, structure it for AI and analytics, and prepare for advanced scheduling and predictive tools. From lessons learned working with early adopters to practical advice on starting small, Tom makes it clear that manufacturing AI is a journey that requires technical expertise, domain knowledge, and cultural change. Whether you are an executive evaluating AI investments, a controls engineer curious about new tools, or a plant manager wondering how to get real results, this episode delivers a balanced, practical, and in-depth perspective on the future of AI in manufacturing.
About the guest About the hosts Dave Griffith is an industrial automation consultant and co-host of Manufacturing Hub. He works with manufacturers and integrators to identify opportunities, manage digital projects, and build future-ready operations. Connect with Dave on LinkedIn: https://www.linkedin.com/in/davegriffith/ If you enjoyed this conversation, make sure to subscribe to Manufacturing Hub for more weekly discussions with industry leaders about automation, digital transformation, and the evolving world of manufacturing. | |||
| Ep. 228 - How to Start OT Cybersecurity ICS Security Fundamentals, Managed Switches Risk Management | 11 sept. 2025 | 01:06:41 | |
In this episode of Manufacturing Hub Podcast, hosts Vladimir Romanov and Dave Griffith sit down with Gavin Dilworth to explore the evolving world of ICS and OT cybersecurity. This is a topic that impacts every sector of manufacturing and critical infrastructure, yet many organizations still struggle with where to start, how to assess risk, and how to balance IT and OT responsibilities. Gavin brings decades of experience in automation engineering and cybersecurity, having worked across energy, oil and gas, water, and manufacturing. He shares his unique journey from being an operator and control systems engineer to becoming a specialist in OT cybersecurity. The conversation spans a wide range of issues, from asset inventory and managed switches to people, process, and technology frameworks that help organizations take the first step toward maturity. We discuss why IT and OT teams often clash and what it takes to bridge the gap. Gavin explains the realities of budgets, the challenges of compliance, and why self-reporting frameworks often fail to reflect true maturity. He also highlights the role of legislation in Europe, rising insurance premiums, and how cybersecurity assessments can influence financial and strategic decisions at the executive level. The episode provides clear insights into best practices such as building a proper asset inventory, structuring security awareness training for OT teams, and applying a risk-based approach to patch management. Gavin also outlines the importance of functional safety, process hazard analysis, and the role of frameworks like ISA/IEC 62443. For engineers, leaders, and decision makers, this conversation makes it clear that cybersecurity is not just a technology problem but a people and process challenge that requires long term discipline and investment. If you want to understand what real world OT cybersecurity looks like, what mistakes to avoid, and how to set a path toward resilience, this episode is packed with valuable takeaways. Timestamps References mentioned in this episode About the hosts Dave Griffith is an experienced systems integrator, consultant, and advisor in the industrial automation space. He has worked with manufacturers across multiple sectors, helping organizations align technology with business strategy. About the guest | |||
| Ep. 229 - Manufacturing Architecture Explained Every Engineer and Plant Manager Needs to Know Today | 29 août 2025 | 01:18:25 | |
In this episode of Manufacturing Hub, Vlad and Dave take a deep dive into one of the most critical yet often overlooked aspects of modern manufacturing: network and systems architecture. Too often manufacturers focus on SCADA, MES, and control layers without recognizing that the architecture beneath them is the foundation that determines whether a facility can scale, connect new equipment, and maintain reliability. Architecture touches everything from plant floor PLCs and HMIs to edge devices, managed switches, firewalls, historians, and enterprise-level systems. We begin the conversation by unpacking what “architecture” actually means in manufacturing environments. Is it the hardware, switches, and cables? Is it the way new machines are integrated into existing plants? Or is it the broader strategy of ensuring that data, safety, and scalability are protected? The answer, as both Vlad and Dave explain, is that it is all of these at once. Throughout the discussion, we explore real-world stories where poor architectural decisions led to unplanned downtime, cybersecurity risks, or expensive rework. Vlad shares an example of a palletizer brought online with unmanaged switches and insecure remote access hardware that nearly crippled production until it was properly segmented. Dave recalls his own field experiences, including unusual setups where integrators resorted to improvised remote troubleshooting, highlighting just how creative but fragile some solutions can be. The episode also looks at the evolution of remote access. From the early days of Ewon boxes to modern expectations of secure VPNs, jump boxes, and approved engineering workstations, we discuss what role remote connectivity should play in today’s manufacturing environment. While these solutions can reduce travel time and speed up support, they can just as easily introduce vulnerabilities and trust issues if not carefully managed. From there we move into the technical tradeoffs of device level ring versus star topologies. Vlad explains why he often prefers device level ring to save costs and simplify troubleshooting, while Dave weighs in on the importance of pre-molded cables, managed switches, and long-term maintainability. We also analyze example architectures from Rockwell white papers, pointing out where diagrams align with field best practices and where they differ from what engineers often see in real facilities. Finally, we broaden the perspective by comparing greenfield and brownfield deployments. Greenfield projects allow prime contractors and consultants to design standards up front, but most facilities live in brownfield reality where years of technical debt, unmanaged switches, and ad hoc networks make improvements harder. We also touch on how architecture differs by industry, whether in food and beverage, pharmaceuticals, oil and gas, or distributed environments such as trains or pipelines. The conversation closes with predictions, career advice, and resource recommendations. Vlad stresses that CCNA is still one of the best starting points for engineers who want to understand industrial networking fundamentals, and Dave emphasizes the importance of asking the right questions and learning from experienced peers. Both agree that demand for data, combined with the rise of AI, will continue to stress legacy networks until companies recognize the need for robust, standards-driven architectures. If you work in automation, engineering, IT, or plant management, this episode will give you perspective on why network architecture is not just a technical afterthought but a strategic enabler of digital transformation. Timestamps References Mentioned in this Episode Siemens SPS Atlanta Event: https://new.siemens.com/us/en/company/fairs-events/sps.html Rockwell Automation Architectures and Design White Papers: https://literature.rockwellautomation.com CISSP Official Study Guide: https://www.isc2.org/Certifications/CISSP Winning by Tim Grover: https://www.amazon.com/Winning-Unforgiving-Race-Greatness/dp/1982168862 Cisco CCNA Certification: https://www.cisco.com/c/en/us/training-events/training-certifications/exams/current-list/ccna.html About the Hosts Vlad Romanov is an electrical engineer and consultant with over a decade of experience in manufacturing and industrial automation. His background spans global companies such as Procter & Gamble, Kraft Heinz, and Post Holdings, where he has led modernization projects, SCADA and MES deployments, and digital transformation initiatives. He is the founder of Joltek, a consulting firm helping manufacturers align people, process, and technology to improve operations, and he also leads SolisPLC, an education platform for automation professionals. Connect with Vlad on LinkedIn: https://www.linkedin.com/in/vladromanov Dave Griffith is a manufacturing consultant and co-host of Manufacturing Hub. With extensive experience in controls, systems integration, and business development, Dave has helped manufacturers across industries adopt SCADA, MES, and digital transformation solutions. He frequently shares insights on IT-OT convergence, operational strategy, and leadership in the automation space. Connect with Dave on LinkedIn: https://www.linkedin.com/in/davegriffith Joltek is a consulting and integration firm that helps manufacturers modernize with clarity, strategy, and execution. Built on decades of hands-on experience in engineering, automation, and plant leadership, Joltek bridges the gap between technical complexity and business value. The team is known for uncovering hidden risks in outdated systems, designing scalable IT and OT architectures, and guiding digital transformation initiatives that actually deliver measurable results. Whether it is upgrading control systems, deploying SCADA and MES platforms, or advising on strategic investments, Joltek consistently brings deep expertise and practical solutions that make manufacturing operations more resilient, efficient, and future ready. Listen and Subscribe | |||
| Ep. 223 - Inductive Automation Ignition 8.3 New Siemens Driver Kafka Event Streams Historian Kevin M | 21 août 2025 | 01:06:27 | |
This week on Manufacturing Hub, Vlad Romanov and Dave Griffith are joined by Kevin McClusky, Chief Technology Architect at Inductive Automation. Kevin shares his journey from computer engineering into the world of industrial automation, his early experiences as an HMI developer, and his leadership roles at Inductive Automation that shaped the direction of Ignition software. The conversation takes a deep dive into the newly released Ignition 8.3 beta, exploring the core features that matter most for end users, system integrators, and manufacturers. Kevin discusses the new Siemens driver with symbolic addressing, the internal historian powered by QuestDB, the Kafka and Event Streams module, and the new DevOps capabilities with file system storage, Git integration, and automated deployments. These capabilities are set to change how manufacturers design, deploy, and scale automation systems in real-world production environments. We also preview the Ignition Community Conference (ICC), which is moving to a larger venue this year. Kevin outlines new additions such as the Hub, the CoLab, community design challenges, and the continuation of Prove It sessions. The episode also covers the evolution of the Build-On competition, the growing integrator ecosystem, and Inductive Automation’s continued focus on empowering its community through transparency and collaboration. This episode provides both a technical and strategic look at where Ignition is heading and why it matters for the future of industrial automation. If you are working on digital transformation, UNS, DevOps for OT, or enterprise-scale SCADA and MES, you will not want to miss this discussion. Timestamps References Mentioned in the Episode Ignition 8.3 Beta Release Notes: https://inductiveautomation.com/downloads/release-notes QuestDB: https://questdb.io/ Opto 22: https://opto22.com/ HiveMQ: https://www.hivemq.com/ Flow Software: https://flow-software.com/ Sepasoft MES: https://sepasoft.com/ Soba.ai: https://soba.ai/ About the Hosts Dave Griffith is a manufacturing consultant and digital transformation strategist who helps organizations navigate technology adoption in automation, data, and operations. With a background in engineering and leadership across multiple industries, Dave focuses on helping manufacturers align technology initiatives with business outcomes. About the Guest Manufacturing Hub is a weekly podcast hosted by Vlad Romanov and Dave Griffith, covering digital transformation, automation, data, robotics, and the future of manufacturing. Subscribe to stay ahead in the industry. | |||
| Ep. 216 - Redefining Manufacturing Resilience at Automate 2025 with Digital Twins and Copilot Tools | 18 août 2025 | 00:14:38 | |
Welcome to our special coverage from Automate 2025, recorded directly at the Siemens booth. In this episode of Manufacturing Hub, hosts Vlad Romanov and Dave Griffith sit down with Chris Stevens and Annemarie Breu from Siemens to explore the evolving landscape of manufacturing resilience, digital twins, and automation lifecycle management. This conversation dives into how manufacturers can prepare for disruptions, scale pilot projects into real business outcomes, and adopt technologies that make factories more flexible and robust. Chris highlights the importance of people and processes in delivering exceptional customer experiences, while Annemarie emphasizes how scaling technology deployments creates measurable business impact. Together, they outline how Siemens is helping manufacturers move from isolated pilots to large scale adoption, ultimately strengthening resilience and competitiveness in today’s uncertain environment. We examine the meaning of manufacturing resilience in practice, including how to withstand supply chain shocks, tariffs, and workforce challenges. The discussion also covers workforce empowerment and the need to make manufacturing attractive again, not only by deploying advanced technologies but also by enabling teams to own solutions from the ground up. A major theme is the role of the digital twin. Chris and Annemarie explain why starting in the virtual world is essential to validate designs, optimize processes, and minimize downtime risks. They address how digital twin adoption is becoming more accessible through as a service delivery models and collaborative environments where end users, system integrators, and technology providers all contribute. We also look at the connection between copilot technologies and both operations and engineering. Natural language copilots are enabling operators to troubleshoot equipment quickly and engineers to interact with simulation environments more intuitively. This shift is accelerating adoption while reducing barriers to advanced tools. Finally, the episode touches on automation lifecycle management, drawing parallels to product lifecycle management. By centralizing and version controlling automation artifacts such as PLC programs, HMI projects, and industrial edge applications, Siemens is paving the way for resilient and adaptable operations. If you are curious about the future of resilient manufacturing, digital twins, and adaptive automation, this episode provides both strategic and practical insights. Timestamps 00:00 Introduction live from Automate 2025 at Siemens booth References mentioned in this episode Siemens Digital Industries: https://www.siemens.com/global/en/products/automation.html About the hosts Vlad Romanov is an engineer, consultant, and co host of the Manufacturing Hub Podcast. With over a decade of experience in manufacturing and industrial automation, Vlad has worked with global companies such as Procter and Gamble and Kraft Heinz, focusing on digital transformation, SCADA and MES deployments, and operational excellence. He also leads Joltek, a consulting firm helping manufacturers modernize operations. Learn more at https://www.joltek.com/ Dave Griffith is a consultant and co host of the Manufacturing Hub Podcast. He has extensive experience helping manufacturers and technology companies bridge the gap between strategy and execution, with a focus on scaling digital transformation initiatives. Dave frequently speaks on topics including systems integration, leadership, and the evolving role of technology in industrial operations. About the guests Chris Stevens is responsible for customer experience at Siemens Digital Industries. His focus is on people and processes, ensuring that technology deployments deliver meaningful outcomes, adoption, and long term value for customers. Annemarie Breu leads the Accelerator Deployment Team at Siemens Digital Industries. She specializes in implementing Siemens technologies beyond the pilot stage, scaling adoption, and ensuring that digital solutions create measurable business outcomes. If you enjoy this conversation, make sure to subscribe to Manufacturing Hub for more interviews from Automate 2025 and beyond. | |||
| Ep. 221 - Manufacturing Intelligence: Data Collection, OEE, and Energy Monitoring Case Studies | 14 août 2025 | 01:09:36 | |
In Episode 221 of Manufacturing Hub, hosts Vlad Romanov and Dave Griffith sit down without a guest to share valuable real-world lessons on data collection, manufacturing intelligence, and implementing solutions that deliver measurable ROI. This episode wraps up the month’s theme on manufacturing intelligence by tying together the insights from previous episodes and putting them into the context of real plant-floor projects. Vlad begins with an in-depth story from his time at Procter & Gamble, where he led an energy monitoring project with the ambitious goal of reducing power consumption by 20 percent. He explains the practical challenges of turning a corporate initiative into an actionable plant-level strategy, from limited baseline data to deciding between standalone meters and integrated monitoring solutions. Vlad shares the lessons learned in balancing cost, data ownership, and scalability, and why a more open solution can sometimes offer greater long-term value than proprietary systems. Dave then takes us into the world of pet food manufacturing, where millions of dollars in raw materials can be lost each year due to inaccurate batching and poor measurement practices. He walks through the process of defining the problem, setting up data collection without overhauling legacy systems, and using that information to identify overages, improve tolerances, and design remediation strategies. The conversation dives into practical engineering decisions, such as when to invest in VFDs for precision dosing, when to redesign process equipment, and how to ensure data insights lead to lasting operational changes. The discussion expands into organizational challenges, including why decision-makers often lack actionable visibility into losses, how to present findings in terms of tangible business impact, and the cultural shift required to actually use the data once it is available. Vlad and Dave also explore examples from discrete manufacturing, where OEE tracking and daily direction setting (DDS) meetings help guide capital allocation, continuous improvement initiatives, and team alignment. They share observations on why some facilities succeed with these systems while others fall back into old habits. Timestamps References Mentioned About the Hosts Vlad Romanov works with manufacturers to modernize operations by bridging the gap between legacy systems and today’s technology. He specializes in assessing current states, designing scalable architectures, and implementing solutions across control systems, SCADA, and MES infrastructures. His mission is to help plants run better from a technical and operational standpoint, whether through unlocking critical data from PLCs or leading full-scale digital transformation initiatives. Dave Griffith has over 16 years of experience in automation and manufacturing, with a technical foundation in aviation and aerospace. His work spans from OEM manufacturing to food and beverage production, with a strong focus on data-driven projects that deliver ROI. Dave leads teams at Kaplan to unlock operational data, design integration strategies, and deploy solutions that improve efficiencies and reduce waste. | |||
| Ep. 220 - Data Foundations and Machine Context Protocol in Modern Manufacturing w/ Caleb Eastman | 07 août 2025 | 01:10:42 | |
In Episode 220 of Manufacturing Hub, we welcome back Caleb Flanigan to explore one of the most critical yet least understood topics in the evolution of smart manufacturing: MTP (Module Type Package), MCP (Machine Context Protocol), and how they are becoming essential enablers of safe and scalable AI adoption on the factory floor. Throughout this deep-dive episode, we uncover how these emerging standards form the backbone of adaptive plants: facilities capable of safely orchestrating decisions between humans, machines, and AI models. From OPC UA and AutomationML to edge computing and LLM-driven control systems, Caleb explains the architecture, mindset shifts, and implementation considerations that make this vision a reality. Key topics covered include:
We also touch on organizational psychology, how internal champions get ignored without executive alignment, and the grim future for manufacturers still betting on ice cube relays. Whether you’re a plant engineer, systems integrator, or digital transformation leader, this conversation offers a bold but practical look at how to safely integrate AI into manufacturing control environments: starting with protocols and principles, not just hype. 🧠 Resources Mentioned:
👤 Guest: Caleb Eastman, Siemens ✅ Key Timestamps 00:00 Welcome Back and Wilborn Celebration 03:30 Caleb's Career Journey from Cisco Cert to Siemens 07:40 Why CLI and Networking Skills Matter in OT 10:00 What Is MCP and Why It Matters for Safe AI 13:00 MTP Overview: The USB of Modular Manufacturing 18:00 Why AI Needs Context-Aware Control Layers 21:00 Bridging Human and AI Control Setpoints 24:30 Brownfield Integration with Siemens Machine Proxy 27:00 Making the Case for AI Investment 31:00 The Future of Safe AI in Manufacturing Plants 36:00 Organizational Resistance and Broken Engineers 42:00 When to Walk Away from Legacy-Only Cultures 46:00 Practical MTP Implementation and Mapping 54:00 Who Maintains MTP and How the Standard Is Evolving 58:00 Predictions: LLMs Will Become Obsolete 01:03:00 Hardware Opportunities and Novel Sensor Startups 01:08:00 Final Thoughts and How to Connect with Caleb | |||
| Ep. 218 - How Siemens Is Building the Next Generation of PLCs and Edge Control Systems w/ Bernd | 04 août 2025 | 00:21:46 | |
In this episode of Automate 2025, we welcome Bernd Raithel from Siemens back to the show to discuss the evolution of industrial control systems and the future of manufacturing. As the Head of R&D for Siemens Factory Automation in the US, Bernd shares his unique perspective on bridging legacy PLCs with modern IT infrastructure, enabling software-defined automation, and empowering manufacturers with flexible and scalable digital tools. With deep insights into products like the S7-1200, S7-1500, TIA Portal, Sematic X, and Siemens Industrial Edge, Bernd explores how Siemens is supporting everything from small-scale modernization to large-scale transformation. We cover critical trends shaping the next generation of manufacturing, including the rise of virtual PLCs (vPLCs), integration of AI into control systems, the shift from hardware to software-defined automation, and the challenges of IT and OT convergence. Bernd also highlights the importance of version control, DevOps pipelines, and open edge development in making industrial systems more agile. We wrap up by looking at Siemens' global R&D structure, freemium software models for engineers, and how manufacturers can take their first steps into digital transformation—without boiling the ocean. This is a must-watch conversation for engineers, IT leaders, and decision-makers in the automation space looking to understand what the future of control and connectivity looks like. 🔗 Mentioned Tools and Technologies:
📍 Timestamps: 📚 Learn More:
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| Ep. 219 - Modernizing Industrial Historian for Scalable Manufacturing Data Architecture with Jeroen | 31 juil. 2025 | 00:58:23 | |
Welcome to Episode 219 of Manufacturing Hub. In this episode, we dive into the evolution of industrial data infrastructure with Jeroen Coussement, Founder and CEO of Factry. Factry is building modern historian and MES software platforms that help manufacturers collect, contextualize, and act on operational data at scale. We unpack the critical role of historians in modern manufacturing environments. While traditional historians focused on archiving time-series data, today’s requirements go far beyond that. Jeroen outlines how a modern historian must fulfill three foundational roles: This episode covers: Jeroen also shares why point solutions often lead to fragmentation, and how building a robust data foundation opens the door to advanced tools like AI, unified namespace, and better decision-making. 📍 Guest: Jeroen Coussement, Founder and CEO at Factry 📚 Resources Mentioned: ⏱️ YouTube Timestamps | |||
| Ep. 217 - Reshaping Manufacturing Data Strategy by Connecting Legacy Equipment to Modern Platforms | 24 juil. 2025 | 01:09:25 | |
Data collection is no longer a back-office task. It is now the foundation of manufacturing intelligence. In this episode of Manufacturing Hub, we are joined by Brian Bribe, founder of Mach Controls, to explore the practical realities of modernizing data infrastructure inside manufacturing facilities. Brian brings a frontline perspective to OT architecture and walks us through what it actually takes to connect legacy equipment, build scalable pipelines, and enable true real-time decision-making. We dive deep into Unified Namespace (UNS) principles, the evolution of MQTT and Kafka in industrial settings, and why so many manufacturers struggle to get ROI from new digital systems. From co-op student to founder of a systems integration firm, Brian shares how his early hands-on experience shaped his understanding of controls, business systems, and the gaps in between. Topics include historian layers, challenges with SCADA-based centralization, how to scope a machine connectivity project, practical change management tips, and the path to flattened architectures using modern pub-sub tools. This is a must-watch for engineers, plant managers, and decision-makers looking to make sense of the data revolution inside their factories. 📌 Episode 217 is the first in our July theme focused on Data Collection for Manufacturing Intelligence. 🔗 Learn more about Manufacturing Hub: https://manufacturinghub.live ⏱️ Timestamps | |||
| Ep. 215 - Robotics 2025: Fanuc, KUKA, & the Future of AI-Powered Automation Humanoids Cybersecurity | 17 juil. 2025 | 01:06:03 | |
In this episode of Manufacturing Hub, we welcome back Pawel Krupa, founder of the Future Robotics YouTube channel, to dive deep into the rapidly evolving world of industrial robotics. With over a decade of hands-on experience integrating and programming systems from Fanuc, KUKA, and others, Pawel shares exclusive insights on some of the biggest changes reshaping robotics in 2025. These changes are not just cosmetic updates; they are being driven by new ISO standards and increasing cybersecurity requirements across industrial automation. We explore the hardware and software changes coming to Fanuc’s R-50iA cabinet, including multiple Ethernet ports, enhanced vision systems with built-in lighting, and a groundbreaking integration of Python for native robot programming. KUKA is also undergoing a major transformation with its KC5 slim cabinet and KUKA iiQ OS, a Linux-based control system with new UI, simulation environments, and plug-and-play capabilities. These updates signify a paradigm shift where robots become not only smarter and safer, but far easier to configure, maintain, and upgrade. The conversation expands into one of the most talked-about frontiers in robotics: humanoid robots. Are they just hype or do they have a real role to play in industrial environments? We assess the business case for humanoids, especially in facilities where traditional automation has been financially unjustifiable. From handling tasks like herb sorting in food production to stepping into high-risk environments, humanoids may soon bridge the automation gap in low-throughput, labor-intensive workflows. We also explore how AI is influencing robot deployment, from edge vision systems to cycle time optimization. Pawel outlines how drag-and-drop AI-powered tools are slashing development time for vision systems from hours to minutes, while also lowering the barrier to entry for those without years of machine vision experience. Vision systems that used to require complex calibration and scripting are now being trained on real-time images or CAD models, making robotic integration faster and more accessible than ever. Finally, we close with actionable startup ideas and a bold look into the future of collaborative robots, AI, and hybrid ecosystems of humanoids and industrial arms working side-by-side. If you're in automation, manufacturing, or considering a robotics venture, this episode is packed with strategic insight, technical knowledge, and forward-thinking ideas you won’t want to miss. 🔗 Explore more from Pawel Krupa: https://www.youtube.com/@FutureRobotics ⏱️ Timestamps | |||
| Ep. 214 - Robotics Rewired: Building Smarter Systems for Tomorrow's Factory | 10 juil. 2025 | 01:02:30 | |
Welcome to another episode of Manufacturing Hub! In this week’s episode, we dive deep into the evolving world of robotics with returning guest Sean Dotson, now CEO of Elite Robotics. From building large-scale material handling systems to exploring the future of AI-driven robot programming, Sean shares a candid view of what it really takes to modernize factory operations. We explore: Plus, Sean shares some incredible stories from the field, including building a machine for radioactive seed sorting and handling rocket-propelled grenade components safely with robots. 🔥 Whether you're an engineer, systems integrator, or a manufacturing leader, this episode offers tactical insights and thoughtful strategy. 🔗 Learn more about Sean’s company: https://eliterobotics.com | |||